Miracle-dz/UniFAR-FTUs huggingface dataset:
ENSO and Light-Absorbing Impurities and Their Impact on Snow Albedo in the Sierra Nevada de Santa Marta, Colombia

Snow albedo is an important variable in the coupled atmosphere-earth system at the global level. Moreover, studying its behavior allows us to know the state of the cryosphere. The Sierra Nevada de Santa Marta (SNSM) is a glacier area and the northernmost tropical (10.82° N, 73.75° W) region in South America. It has a height of up to 5775 m.a.sl. , which is the second highest mountain in the world near the marine coast. We analyzed variations in snow albedo related to snow cover, snowfall, temperature, light-absorbing impurities such as blank carbon (BC), organic carbon (OC) and dust, and El Niño—Southern Oscillation (ENSO) phenomenon through 20 years (2000–2020). We mainly use daily data from the Moderate Resolution Imaging Spectroradiometer (MODIS) onboard the Terra and Aqua NASA satellites. Results showed through correlations that snow albedo has decreased due to Land Surface Temperature (55%, p < 0.001), a positive phase of ENSO (42%, p < 0.001) and dust (37%, p < 0.01) in the SNSM. Additionally, a dust negative effect was more evident on the southern side (up to 49%, p < 0.001) of the SNSM. Backward trajectories by the NOAA HYSPLIT model suggest that dust sources would be soil erosion in the surrounding region. Results can help recognize the influence of ENSO and dust in the glacier decrease of the SNSM.
Perceived reasons for paying more for housing in metro Atlanta: Results from the 2018 Metro Atlanta Speaks survey

ABSTRACT Various factors may influence housing prices paid by residents, and these factors can be grouped into the demand- or supply-side factors. However, the empirical literature has not adequately investigated whether or not residents perceive that they pay more for housing, and if so, whether paying more is associated with the demand-side factors such as housing attributes or neighborhood/locational amenities, or supply-side factors such as a lack of affordable housing alternatives. Using the 2018 Metro Atlanta Speaks survey, we find that millennials, Blacks or African Americans, Hispanics or Latinos, residents with children, and relatively higher-income residents perceived that they are paying more because of the demand-side factors such as housing attributes or neighborhood/locational amenities. Conversely, working-age residents, females, high school graduates or less, and renters perceived that they are paying more due to the supply-side factors such as a lack of affordable housing alternatives. In a situation where residents are to choose one factor associated with housing, millennials and Blacks or African Americans prefer the quality of housing, relatively higher-income residents prefer local schools, new residents to the area prefer neighborhoods, and Hispanics or Latinos and employed residents prefer location over any other factors.
Temperature and Humidity Controlling System for Baby Incubator

Baby incubator is very important to keep the newborn’s body temperature especially for premature babies. The research aimed to design a baby incubator with controlled temperature and humidity. The incubator is designed to have a length of 60 cm, a width of 40 cm, and a height of 30 cm. System of baby incubator will automatically turn on or turn off the fan and or heating in accordance with the normal range of temperature and humidity in the incubator. The normal limits of temperature used is 33°C to 35°C. While the normal limits of air humidity in the incubator used is between 40% and 60%. Data acquisition system consists of temperature and humidity sensor, microcontroller ATmega8535, fan, heater, and LCD. LCD is used to display the results of measurements of temperature and humidity. Heater is used to regulate the temperature in the incubator. While fan is used to regulate the humidity in the incubator. Test results show that the heater will turn on if the temperature is below the limits of 33°C. While the fan will turn on if the humidity is above 60%
Effect of Nickel–Phosphorus and Nickel–Molybdenum Coatings on Electrical Ablation of Small Electromagnetic Rails

The electromagnetic rail catapult is a device that converts electrical energy into kinetic energy, which means that the strength of electrical energy directly affects the muzzle speed of armature. In addition, the electrical conductivity, electromagnetic rails and armature surface roughness, and the holding force of the rail are influencing factors that cannot be ignored. However, the electric ablation on the surface of the electromagnetic rails caused by high temperatures seriously affects the service life performance of the electromagnetic catapult system. In this study, electrochemically deposited nickel-phosphorus and nickel-molybdenum alloy coatings are plated on the surface of electromagnetic iron rails and their effects on the reduction of ablation are investigated. SEM (scanning electron microscopy) with EDS (energy dispersive spectroscopy) detector, XRD (X-ray diffraction), 3D optical profiler, and Vickers microhardness tester are used. Our results show that the sliding velocity of the armature decreases slightly with the increased roughness of the rail coating surface. On the other hand, the area of electric ablation on the rail surface is inversely related to the hardness of the rail material. The electrically ablated surface areas of the rails are in: annealed nickel–molybdenum < nickel–molybdenum < annealed nickel–phosphorus < nickel–phosphorus < iron material. Heat treatment at 400 and 500 °C, respectively for Ni–P and Ni–Mo alloys, significantly increases hardness due to the precipitation of intermetallic compounds such as Ni3P and Ni4Mo phases. Comprehensive data analysis shows that the annealed nickel–molybdenum coating has the best electrical ablation wear resistance. The possible reason for that might be attributed to the high hardness of the heat-treated nickel–molybdenum coating. In addition, the thermal resistance capability of molybdenum is better than that of phosphorus, which might also contribute to the high wear resistance to electric ablation.
Analysis of Hospital Information System Implementation Using the Human-Organization-Technology (HOT) Fit Method: A Case Study Hospital in Indonesia

Background and purpose: The implementation of Hospital Information System (HIS) is important to achieve strategic objectives based on quality services. For this reason, an evaluation is needed to find out how the benefits of HIS in the hospital work unit. This study uses the evaluation framework of Human, Organization, Technology (HOT) Fit which was introduced by Yusof in 2008. Methods: This research method was carried out using a mixed method approach where the quantitative approach was processed by using Partial Least Square. The sample was obtained through proportionate stratified random sampling, namely 201 respondents who were employees of HIS users in MHJS hospital. The research instrument used a questionnaire and was measured using a Likert scale Results: Based on the results of the t-statistic test, there is a misfit which appears in the insignificant direct effect between service quality on user satisfaction (p-value 0.062), service quality on system use (p-value 0.063), organizational structure for system use (p-value 0.492) and user satisfaction with system usefulness (p-value 0.188). Conclusions: It is necessary to improve the service quality because does not significantly influence user satisfaction and system use. System quality provides a dominant influence on user satisfaction, the use of systems and organizational structures so that management plays a very important role in the implementation of HIS in MHJS hospital.
A statistical approach for the automatic identification of the start of the chain of events leading to the disruptions at JET

This paper reports an algorithm to automatically identify the chain of events leading to a disruption, evaluating the so-called reference warning time. This time separates the plasma current flat-top of each disrupted discharge into two parts: a non-disrupted part and a pre-disrupted one. The algorithm can be framed into the anomaly detection techniques as it aims to detect the off-normal behavior of the plasma. It is based on a statistical analysis of a set of dimensionless plasma parameters computed for a selection of discharges from the JET experimental campaigns. In every data-driven model, such as the generative topographic mapping (GTM) predictor proposed in this paper, it is indeed necessary to label the samples needed for training the model itself. The samples describing the disruption-free behavior are extracted from the plasma current flat-top phase of the regularly terminated discharges. The disrupted space is described by all the samples belonging to the pre-disruptive phase of each disruptive discharge in the training set. Note that a proper selection of the pre-disruptive phase plays a key role in the prediction performance of the model. Moreover, these models, which are highly dependent on the training input space, may be particularly prone to degradation as the operational space of any experimental machine is continuously evolving. Hence, a regular schedule of model review and retrain must be planned. The proposed algorithm avoids the cumbersome and time-consuming manual identification of the warning times, helping to implement a continuous learning system that could be automated, despite being offline. In this paper, the automatically evaluated warning times are compared with those obtained with a manual analysis in terms of the impact on the mapping of the JET input parameter space using the GTM methodology. Moreover, the algorithm has been used to build the GTM of recent experimental campaigns, with promising results.
Preliminary evaluation of polymeric Fe‐ and Al‐modified clays as adsorbents for heavy metal removal in water treatment

This paper assesses the potential of modified montmorillonite clays as low-cost adsorbents/ion-exchangers for the removal of trace level heavy metals (Cd, Cu, Ni, Pb and Zn) from potable water. Modification of the montmorillonites resulted in the exchange of the interlayer calcium ions for the polymeric species. One unmodified montmorillonite and three polymeric Fe- and Al-modified montmorillonites have been evaluated with respect to their selectivity and uptake performance. All of the clays are selective for Pb and Cu adsorption from aqueous solutions at the mildly acidic pH range in which the experiments were performed (pH 5.5–6). Polymeric iron- and polymeric Al/Fe-modified clays had comparatively great affinities for all the metals studied, whilst the original and polymeric Al modified clays had relatively lower affinities. Only the uptake of Pb and Cu could be correlated with physical properties such as clay surface area. The metal selectivity could be correlated to the type of intercalated polymeric Fe and Al species of the modified clays.
Clinical value of docetaxel plus cisplatin (TP) induction chemotherapy followed by TP concurrent chemoradiotherapy in locoregionally advanced nasopharyngeal carcinoma

Objective: To investigate the clinical value of induction chemotherapy (IC) with docetaxel plus cisplatin (TP) followed by concurrent chemoradiotherapy (CCRT) with TP in locoregionally advanced nasopharyngeal carcinoma (NPC). Methods: A total of 544 patients with locoregionally advanced NPC that was newly diagnosed from January 2009 to December 2015 were included in this study. Among these patients, 251 were treated with TP induction chemotherapy followed by CCRT with cisplatin (DDP) alone (TP + DDP group), 167 were treated with TP followed by CCRT with TP (TP + TP group), and 126 were treated with docetaxel, DDP and fluorouracil (TPF) followed by CCRT with DDP alone (TPF + DDP group). Overall survival (OS), distant metastasis-free survival (DMFS), progression-free survival (PFS) and locoregional relapse-free survival (LRRFS) were analyzed using the Kaplan-Meier method and a Cox proportional hazards model. Results: Survival analysis showed that the 5-year OS, PFS and DMFS rates in the TP + DDP group were significantly lower than those in the TP + TP group after propensity score matching (PSM). Multivariate analysis revealed that CCRT with TP was an independent prognostic factor for OS, PFS and DMFS. During CCRT, the incidence rates of grade 3/4 nausea/vomiting, oral mucositis, leukocytopenia and neutropenia were significantly increased in the TP + TP group compared with the TP + DDP group (all P < 0.05). To further explore the value of TP + TP, we performed PSM again with the TPF + DDP group. After PSM, there were 100 patients in each group. Survival analysis showed no significant differences in the 5-year OS, PFS, DMFS and LRRFS rates between the two groups. During IC and CCRT, the rate of grade 3/4 nausea/vomiting in the TPF + DDP group was higher than that in the TP+TP group (9.0% vs. 2.0%, P = 0.030; 18.0% vs. 8.0%, P = 0.036, respectively). No significant difference in the incidence of grade 3/4 hematologic toxicity was found between the two groups (all P > 0.05). Conclusion: TP + TP can reduce the distant metastasis of locoregionally advanced NPC and improve OS compared with TP + DDP; TP + TP has the same effect as TPF + DDP and is clinically feasible.
Autonomous Vehicle Fuel Economy Optimization with Deep Reinforcement Learning

The ever-increasing number of vehicles on the road puts pressure on car manufacturers to make their car fuel-efficient. With autonomous vehicles, we can find new strategies to optimize fuels. We propose a reinforcement learning algorithm that trains deep neural networks to generate a fuel-efficient velocity profile for autonomous vehicles given road altitude information for the planned trip. Using a highly accurate industry-accepted fuel economy simulation program, we train our deep neural network model. We developed a technique for adapting the heterogeneous simulation program on top of an open-source deep learning framework, and reduced dimension of the problem output with suitable parameterization to train the neural network much faster. The learned model combined with reinforcement learning-based strategy generation effectively generated the velocity profile so that autonomous vehicles can follow to control itself in a fuel efficient way. We evaluate our algorithm’s performance using the fuel economy simulation program for various altitude profiles. We also demonstrate that our method can teach neural networks to generate useful strategies to increase fuel economy even on unseen roads. Our method improved fuel economy by 8% compared to a simple grid search approach.
Genital infection by Aerococcus viridans in a captive african elephant (Loxodonta africana)

ABSTRACT: Aerococcus viridans is an emerging pathogen for humans and livestock animals, mainly associated with genitourinary infections cases. Its occurrence in wild mammals has never been reported. The aim of this study was to determine the etiological agent associated with clinical a case of a genital infection in a female African elephant (Loxodonta africana). Phylogenetic analysis and antimicrobial susceptibility profile of the isolate were also addressed. The animal presented frequent cases of genital infection with intermittent white secretion. Purulent secretion was sampled and submitted to bacteriological exam. The isolate obtained was thus identified by phenotypic and molecular methods as A. viridans and was found to be similar to human pathogenic isolates in BLASTn and phylogenetic analysis. The isolate was sensitive to almost all antimicrobials evaluated, presenting resistance to ciprofloxacin and norfloxacin. This is the first report of occurrence of A. viridans infection in the genital tract of an African elephant.
Motion Control in Magnetic Microrobotics: From Individual and Multiple Robots to Swarms

Magnetic microrobotics has undergone approximately 20 years of development, and the robotics and control communities have contributed significant theoretical and practical results to the motion control aspects of this field. This article introduces fundamental motion principles covering individual, multiagent, and swarm control and critically reviews the state of the art along with representative results. It then describes closed-loop control (an important part of this field), including the system structure, current motion planning and control methods, and current feedback approaches. As the development of motion control in magnetic microrobotics is far from complete, especially for swarm control, its current limitations are discussed. Finally, we conclude with several challenges and future research directions.
Hybrid electrostatic and gecko-inspired gripping pads for manipulating bulky, non-smooth items

We present hybrid electrostatic and gecko-inspired gripping pads that help robots to lift and carry bulky objects. The directional, gecko-inspired adhesive provides a controllable shear force with low normal force, providing a very high effective coefficient of friction so that items like bags full of groceries and heavy cardboard boxes can be lifted using only 1–2 N of squeezing force. The addition of electrostatics helps the pads to conform to non-smooth surfaces, providing substantially higher shear forces than with gecko-inspired adhesives alone. The electrostatic effect is enhanced by doping the silicone rubber adhesive material with calcium copper titanate (CCTO), except at the contacting faces of the adhesive microstructures, where a smooth surface finish is important for adhesion. We describe the multimaterial fabrication process used to create the new hybrid adhesive and present the results of robotic lifting experiments with non-smooth bulky items.
Water-Energy Nexus: A Pathway of Reaching the Zero Net Carbon in Wastewater Treatment Plants

The water-energy nexus, together with the need for sustainable management of these interconnected resources, has attracted growing attention from the scientific community. This paper focuses on this nexus from the point of view of the energy that is required by wastewater treatment plants, which are intensive energy consumers and major emitters of greenhouse gases. The main objective of the study is to investigate the possible use of a wastewater plant’s internal chemical, potential, and kinetic energy, and the addition of external renewable technologies with a view to achieving clean energy consumption and reducing greenhouse gas emissions. For this purpose, an analysis is made of the feasibility of introducing alternative technologies—anaerobic digestion, hydraulic turbines, wind turbines, and photovoltaic modules— to meet the plant’s energy needs. The plant chosen as case study (Jinamar plant, Canary Islands, Spain) has an energy consumption of 2956 MWh/year, but the employed methodological framework is suitable for other plants in locations where the renewable energy potential has previously been analyzed. The results show that a renewable energy production of 3396 MWh/year can be obtained, more than enough to meet plant consumption, but also confirm the need for an energy storage system, due to seasonal variability in energy resource availability. In terms of climate change mitigation, the emission of 2754 tons/year of greenhouse gases is avoided. In addition, the economic viability of the proposed system is also confirmed.
The dominant leg is more likely to get injured in soccer players: systematic review and meta-analysis

In soccer (football), dominant limb kicking produces higher ball velocity and is used with greater frequency than the non-dominant limb. It is unclear whether limb dominance has an effect on injury incidence. The purpose of this systematic review with meta-analysis is to examine the relationship between limb dominance and soccer injuries. Studies were identified from four online databases according to PRISMA guidelines to identify studies of soccer players that reported lower extremity injuries by limb dominance. Relevant studies were assessed for inclusion and retained. Data from retained studies underwent meta-analyses to determine relative risk of dominant versus non-dominant limb injuries using random-effects models. Seventy-four studies were included, with 36 of them eligible for meta-analysis. For prospective lower extremity injury studies, soccer players demonstrated a 1.6 times greater risk of injury to the dominant limb (95% CI [1.3–1.8]). Grouped by injury location, hamstring (RR 1.3 [95% CI 1.1–1.4]) and hip/groin (RR 1.9 [95% CI 1.3–2.7]) injuries were more likely to occur to the dominant limb. Greater risk of injury was present in the dominant limb across playing levels (amateurs RR 2.6 [95% CI 2.1–3.2]; youths RR 1.5 [95% CI 1.26–1.67]; professionals RR 1.3 [95% CI 1.14–1.46]). Both males (RR 1.5 [95% CI 1.33–1.68)] and females (RR 1.5 [95% CI 1.14–1.89]) were more likely to sustain injuries to the dominant limb. Future studies investigating soccer injury should adjust for this confounding factor by using consistent methods for assigning limb dominance and tracking use of the dominant versus non-dominant limb.
Simultaneous Determination of the Complexing Capacity and Conditional Stability Constant of Soluble Copper(II) Complexes in Natural-Water Samples by Using a Chelate Extraction Technique

Based on a back-extraction of bis(4,4,4-trifluoro-1-(2-thienyl)-1,3-butanedionato)copper(II), a method for the simultaneous determination of the copper(II) complexing capacity of natural water and the conditional stability constant of copper(II) complex with naturally occurring ligands was developed. The feasibility of the proposed method was confirmed using nitrilotriacetic acid and ethylenediamine- N , N ′-dipropionic acid instead of naturally occurring ligands. It was then applied to a pond-water sample. The results indicated that two types of copper(II) complexes having different stabilities were formed upon the addition of copper(II) to the sample. By using the copper(II) complexing capacity and the conditional stability constant, the distribution of copper(II) species in pond water was calculated. It was found that most of the copper(II) in pond water exists as a complex with a naturally occurring ligand, and that the concentration of free copper(II) ion is extremely low.
Identification, characterization and interaction studies of Di19-2 gene from Gossypium arboreum

Cotton is the most vital source of fiber and food industry. Limited availability of water results in the limited growth of plants. Drought responsive genes have been explored in several plants to be utilized for overcoming the dilemma of limited availability of water. Over expression of drought responsive genes to develop drought resistant cultivars is a promising strategy to combat drought stress. On exposure to drought, several genes linked to drought are activated and many of them are regulated by transcription factors. Recent developments in bioinformatics have made identification and In silico characterization of the genes possible. Di19 is the drought responsive transcription factor, which is involved in the drought tolerance pathways. This gene has been observed to interact with several other genes in the drought tolerance pathway in the plants. In the present study, this gene was amplified in Gossypium arboreum cultivar FDH-786 using primers based on GhDi19 gene sequence, further sequenced and named as GaDi19 (Accession No. KP297805). Sequence of GaDi19 showed highest similarity with GhDi19 (97%). Protein 3D model for GaDi19 was determined and Ramanchandran plot indicated that 98% residues were in favored region. Further modelling and interaction study revealed that GaDi19 interact with pathogen related PR1, PR2 and PR5. Interaction of GaDi19 with protein encoded by other genes i.e Di19 from other plant species and EREB1 and EREB2 was also determined. Further interaction studies of PR1, PR2 and PR5 revealed activation of AP2/EREBP, DREB1a, DREB1b and WRKY3 to develop the drought tolerance in plants, which is a novel finding and has not been reported earlier. This study will lay a foundation for researchers to get insight into genes responsible for drought and their involvement in the pathways of drought tolerance.