Miracle-dz/UniFAR-FTUs huggingface dataset:
Particle-Based Workflow for Modeling Uncertainty of Reactive Transport in 3D Discrete Fracture Networks

Fractures are major flow paths for solute transport in fractured rocks. Conducting numerical simulations of reactive transport in fractured rocks is a challenging task because of complex fracture connections and the associated nonuniform flows and chemical reactions. The study presents a computational workflow that can approximately simulate flow and reactive transport in complex fractured media. The workflow involves a series of computational processes. Specifically, the workflow employs a simple particle tracking (PT) algorithm to track flow paths in complex 3D discrete fracture networks (DFNs). The PHREEQC chemical reaction model is then used to simulate the reactive transport along particle traces. The study illustrates the developed workflow with three numerical examples, including a case with a simple fracture connection and two cases with a complex fracture network system. Results show that the integration processes in the workflow successfully model the tetrachloroethylene (PCE) and trichloroethylene (TCE) degradation and transport along particle traces in complex DFNs. The statistics of concentration along particle traces enables the estimations of uncertainty induced by the fracture structures in DFNs. The types of source contaminants can lead to slight variations of particle traces and influence the long term reactive transport. The concentration uncertainty can propagate from parent to daughter compounds and accumulate along with the transport processes.
Electricity Consumption in Industrial Segment on Time Series Analysis

The economic growth in each country mostly depends on their industrial sector which always require an electrical energy. Therefore, power consumption should have some relations with changing of the economic trends that are represented by trends of the stock price in each an industrial sector for this paper. The relations also depend on each period and place. To prove the relations, our experiments are represented by two example companies in the difference industry sector, i.e. Company A (an automobile part factory) and Company B (a food processing factory), and consist of two phases using Artificial Neural Network(ANN). In Phase-I, monthly unit stock prices are predicted in the normal period by using 2 feature inputs of data sets. The first input is the history of their stock prices from Bloomberg website in the past 5 years. And another is their power consumption in the past 5 years and collected by PEA (Provincial Electricity Authority) of Thailand government enterprise in the utility sector. In Phase-II, we estimate the same thing in Phase-I but focus on Thailand flood 2011 period or hazardous period. And then we conduct cross-checking between the two examples with a Disaster Signal (DS). Finally, the performance showed up to 37.25% and 64.55% in Phase-I and Phase-II respectively. So our experiment can completely prove the relations that mentioned over the period.
BAYESIAN AND CLASSICAL MODELS TO ESTIMATE ABOVEGROUND STAND BIOMASS IN AN OAK SILVOPASTORAL SYSTEM

Forest biomass is one of the key variables in understating structural and functional dynamics of ecosystem processes. In this paper, four different empirical models derived by Bayesian and classical theory had been applied to the diameter distribution of valonia oak (Quercus ithaburensis subsp. macrolepis) trees, dominating a silvopastoral ecosystem located at western part of central Greece, to estimate aboveground woody biomass (M). The novelty of the present article is based on the fact that error variance in M, for each plot and for each model, is also reported along with the average value. Prediction intervals on M are rarely being reported in forest biomass studies. Results indicated that M ranged from 15.60 to 164.23 ton/ha across 40 plots. At forest scale, the average M value derived by four models amounted to 445,848 ton and divided by two defines the aboveground carbon stock value in oak trees. Even though the applied models obtained quite similar mean plot biomass values, prediction intervals differed substantially. Log-linear and noninformative Bayesian approaches provided very large variation in predicted values (e.g., reaching up to 102% difference in plot 31), while non-linear regression equation provided unrealistic (near to zero biomass in plot 35) values. It is therefore concluded that the informative Bayesian model seems to provide biologically sound results and may be preferred over the rest of the methods, but further research is needed to take place in the studied ecosystem to reach unambiguous conclusions. The output of this study may be used, in conjunction to older plot inventories, to deeper understand the carbon dynamics in the specific forest. The adaptation of such an approach may provide qualitative and certified outputs for the fulfilment of Greek reporting obligations in international treaties on climate change. Finally, the obtained M values at plot level may be incorporated into the process of forest management plan in order to set appropriate objectives for the sustainable development of valonia oak stands.
Analysis of Software Project Complexity Factors of Large Scale Systems and Their Impacts on Core Knowledge Areas of Software Project Management

Software project complexity increases day by day because the software engineering products is being used in the solution of more technically difficult problem and the size of project continuous to grow. The increase complexity causes to high numbers of software project failures in term of time, cost and quality. The main question regarding to this problem is how to handle or cope with this complexity. There is no single way to handle this, software engineer uses different perspective to handle complexity without affecting the overall project performance. A management perspective recognizes that the success of complex project requires good project management. A technically perspective reveals new paradigms for software development i.e.; object oriented and formal methods etc. and software engineer also look for automation perspective in order to reduce the complexity issues. In this paper we will find out the main software project complexity factors by focusing on the management aspects of software project development and also the problems of managing complexity in software engineering products from these different perspectives. The paper is divided in three main sections; paradigms of software development, project management in term of time, cost and quality and third one is automated support that includes methods and tools used to manage the complexity.
Automatic Hybrid Attack Graph (AHAG) Generation for Complex Engineering Systems

Complex Engineering Systems are subject to cyber-attacks due to inherited vulnerabilities in the underlying entities constituting them. System Resiliency is determined by its ability to return to a normal state under attacks. In order to analyze the resiliency under various attacks compromising the system, a new concept of Hybrid Attack Graph (HAG) is introduced. A HAG is a graph that captures the evolution of both logical and real values of system parameters under attack and recovery actions. The HAG is generated automatically and visualized using Java based tools. The results are illustrated through a communication network example.
Quantifying Age-Related Differences of Ankle Mechanical Properties Using a Robotic Device

A deep analysis of ankle mechanical properties is a fundamental step in the design of an exoskeleton, especially if it is to be suitable for both adults and children. This study aims at assessing age-related differences of ankle properties using pediAnklebot. To achieve this aim, we enrolled 16 young adults and 10 children in an experimental protocol that consisted of the evaluation of ankle mechanical impedance and kinematic performance. Ankle impedance was measured by imposing stochastic torque perturbations in dorsi-plantarflexion and inversion-eversion directions. Kinematic performance was assessed by asking participants to perform a goaldirected task. Magnitude and anisotropy of impedance were computed using a multipleinput multiple-output system. Kinematic performance was quantified by computing indices of accuracy, smoothness, and timing. Adults showed greater magnitude of ankle impedance in both directions and for all frequencies, while the anisotropy was higher in children. By analyzing kinematics, children performed movements with lower accuracy and higher smoothness, while no differences were found for the duration of the movement. In addition, adults showed a greater ability to stop the movement when hitting the target. These findings can be useful to a proper development of robotic devices, as well as for implementation of specific training programs.
Reconstruction of rainfall fields by spatio-temporal models using radar and raingauges measurements in Southern Italy

In response to the drought experienced in Southern Italy a Rain enhancement project has been set and developed during several years. The initiative was taken with the purpose of applying Israeli methods and rain enhancement technology in Puglia and other regions of Southern Italy. The aim of this study is to accomplish a support to the evaluation of the experimental part of the Rain Project which was conducted for the period 1986-1994. In particular our aim is to reconstruct rainfall fields combining two source of data: rainfall intensity and radar reflectivity. In 1992, a high density network of 80 automated raingauges with high time (10 minutes) and space ( 10 km inter-gauge spacing) resolution was installed in the experimental area; moreover a C-band digital weather radar, scanning the whole area every five minutes, was introduced. Radar raingauge systems are increasingly used to reconstruct rainfall fields since they are able to provide spatially continuous images of precipitation for short and regular time intervals. On the other hand, ground raingauges monitoring network located in a set of sites within the study area provide more accurate, direct (punctual) estimates of rainfall intensity. However the coverage of the study area by such raingauges is spatially sparse in comparison to the grid on which radar reflectance is recorded. In this work we investigate the relationship between radar reflectance and rainfall intensity in order to build a model able to provide estimates of rainfall intensity over a region larger then the one covered by the ground raingauges network. We compare several approaches to the reconstruction of the rainfall field: the first one is based on the state-space approach proposed in (Brown et al. 2001), the second one uses a Kriging with external drift technique and the third one is built on a complex Bayesian model as proposed in Mardia and Sahu (2004).
Influence of Mixed Valence on the Formation of Oxygen Vacancy in Cerium Oxides

Ceria is one of the most important functional rare-earth oxides with wide industrial applications. Its amazing oxygen storage/release capacity is attributed to cerium’s flexible valence conversion between 4+ and 3+. However, there still exists some debate on whether the valence conversion is due to the Ce-4f electron localization-delocalization transition or the character of Ce–O covalent bonds. In this work, a mixed valence model was established and the formation energies of oxygen vacancies and electronic charges were obtained by density functional theory calculations. Our results show that the formation energy of oxygen vacancy is affected by the valence state of its neighboring Ce atom and two oxygen vacancies around a Ce4+ in CeO2 have a similar effect to a Ce3+. The electronic charge difference between Ce3+ and Ce4+ is only about 0.4e. Therefore, we argue that the valence conversion should be understood according to the adjustment of the ratio of covalent bond to ionic bond. We propose that the formation energy of oxygen vacancy be used as a descriptor to determine the valence state of Ce in cerium oxides.
Assessment of Thermosonication as Postharvest Treatment Applied on Whole Tomato Fruits: Optimization and Validation †

Tomatoes are a popular and rich fruit due to their nutritional and bioactive composition as vitamins, antioxidants, and phenolics contributing to the promotion of consumer health. For this reason, emerging postharvest technologies need to be evaluated to achieve the maintenance of sensorial and quality-related characteristics, like color and texture, while aiding to fruit decontamination. Optimization of thermosonication as postharvest treatments on whole, mature-green tomatoes (cv. “Zinac”) to improve quality (color, texture, total phenolic content, and weight loss) was performed by response surface methodology. Temperature (32–48 °C), treatment time (13–47 min), and storage period at 10 °C (1–15 days) at constant ultrasound frequency (45 kHz; 80% power level), were the independent variables. In general, thermosonication delayed tomato color changes while achieving total phenolic content increase and good overall quality. Three optimal thermosonication conditions were selected and validated (32 °C-13 min, 35 °C-20 min and 40 °C-30 min). The most suitable thermosonication condition that promoted a longer storage while keeping a high-quality standard was at 40 °C during 30 min. This study demonstrated that thermosonication provides an effective alternative methodology to guarantee tomato quality without significant change during the expected postharvest period.
Analysis of Raindrop Size Distribution Characteristics in Permafrost Regions of the Qinghai–Tibet Plateau Based on New Quality Control Scheme

Raindrop size distribution (DSD) can reflect the fundamental microphysics of precipitation and provide an accurate estimation of its amount and characteristics; however, there are few observations and investigations of DSD in cold, mountainous regions. We used the second-generation particle size and velocity disdrometer Parsivel2 to establish a quality control scheme for raindrop spectral data obtained for the Qinghai–Tibet Plateau in 2015. This scheme included the elimination of particles in the lowest two size classes, particles >10 mm in diameter and rain rates <0.01 mm∙h−1. We analyzed the DSD characteristics for different types of precipitation and rain rates in both permafrost regions and regions with seasonally frozen ground. The precipitation in the permafrost regions during the summer were mainly solid with a large particle size and slow fall velocity, whereas the precipitation in the regions with seasonally frozen ground were mainly liquid. The DSD of snow had a broader drop spectrum, the largest particle size, the slowest fall velocity, and the largest number of particles, followed by hail. Rain and sleet shared similar DSD characteristics, with a smaller particle size, slower velocity, and smaller number of particles. The particle concentration for different classes of rain rate decreased with an increase in particle size and decreased gradually with an increase in rain rate. Precipitation with a rain rate >2 mm∙h−1 was the main contributor to the annual precipitation. The dewpoint thresholds for snow and rain in permafrost regions were 0 and 1.5 °C, respectively. The dewpoint range 0–1.5 °C was characterized by mixed precipitation with a large proportion of hail. This study provides valuable DSD information on the Qinghai–Tibet Plateau and can be used as an important reference for the quality control of raindrop spectral data in regions dominated by solid precipitation.
A Cancer Theory: The Central Nervous System’s Adaptive Changes Make Chronic Diseases Incurable

We examined special roles of the Central Nervous System (CNS) in an attempt to resolve the puzzle that chronic diseases cannot be cured in medicine. By exploring a skill-learning model, we found that the CNS is able to remember certain information reflecting biochemical and cellular (B&C) processes in the body. From the skill-using ability, we found that the CNS is able to control basic B&C processes that drive and power the skill. From the ability to adjust forces and moving direction of body parts, we infer that the CNS is able to adjust B&C processes that control physical acts. From this controlling capability, we inferred that the CNS must also store certain information on the baseline B&C processes, is able to up-regulate or down-regulate the B&C processes, and make comparisons in performing its regulatory functions. We found that chronic diseases are the results of deviated baseline B&C processes, the CNS plays a role in maintaining deviated baseline B&C processes, and protects the body state of a fully developed disease. The three CNS roles can explain that cancer progresses with increasing malignancy, cancer quickly returns after a surgery, cancer cells repopulate after chemotherapy and radiotherapy, cancer patients develop drug resistance inevitably, immune cells rebound after suppression, etc. We further showed that long-term exercises generally can correct part of the departures in B&C processes and thus help to reverse chronic diseases. Finally, we propose strategies for resetting the CNS’ state memory as an essential condition for curing chronic diseases and cancer.
Sub-Standard Pharmaceutical Services in Private Healthcare Facilities Serving Low-Income Settlements in Nairobi County, Kenya

Background: Quality pharmaceutical services are an integral part of primary healthcare and a key determinant of patient outcomes. The study focuses on pharmaceutical service delivery among private healthcare facilities serving informal settlements within Nairobi County, Kenya and aims at understanding the drug procurement practices, task-shifting and ethical issues associated with drug brand preference, competition and disposal of expired drugs. Methods: Forty-five private facilities comprising of hospitals, nursing homes, health centres, medical centres, clinics and pharmacies were recruited through purposive sampling. Structured electronic questionnaires were administered to 45 respondents working within the study facilities over an 8-week period. Results: About 50% of personnel carrying out drug procurement belonged to non-pharmaceutical cadres namely; doctors, clinical officers, nurses and pharmacy assistants. Drug brand preferences among healthcare facilities and patients were mainly pegged on perceived quality and price. Unethical business competition practices were recorded, including poor professional demeanour and waiver of consultation fees veiled to undercut colleagues. Government subsidized drugs were sold at 100% profit in fifty percent of the facilities stocking them. In 44% of the facilities, the disposal of expired drugs was not in conformity to existing government regulatory guidelines. Conclusions: There is extensive task-shifting and delegation of pharmaceutical services to non-pharmaceutical cadres and poor observance of ethical guidelines in private facilities. Strict enforcement of regulations is required for optimal practices.
Differential Allelic Richness between Malus sylvestris L. and Malus × domestica Borkh. from Finland as a Measure of Genetic Loss

European wild apple (Malus sylvestris L.) is the only Malus wild species native to Europe which is a relative of cultivated apples (Malus × domestica Borkh.). It grows on forests’ edges, farmland hedges, and marginal sites; by living in those scattered meta-populations, it is exposed to genetic erosion in relation to hybridization and habitat degradation. In Finland, it grows at the northern edge of its distribution in Europe and is considered as a near-threatened taxon requiring urgent conservation. In order to evaluate the molecular genetic diversity of M. sylvestris, five populations including 43 trees were analyzed using 15 microsatellite markers. Additionally, a similar number of samples from cultivated apples, which are common to the same region, was included in order to estimate gene diversity gaps and give an insight into putative hybridization. European wild apple in Finland proved to be populationally structured, and seems not to be threatened by introgression events from its cultivated relative. They were all separated into different clusters, except for one individual. However, urgent conservation is indeed needed, especially due to the very low total number of trees (four) in some of the analyzed populations. These populations should be restored in order to enable permanent access to the wild relatives’ diversity, as they might be a critical source of gene variants for future needs.
The Association of Ascorbic Acid, Deferoxamine and N-Acetylcysteine Improves Cardiac Fibroblast Viability and Cellular Function Associated with Tissue Repair Damaged by Simulated Ischemia/Reperfusion

Acute myocardial infarction is one of the leading causes of death worldwide and thus, an extensively studied disease. Nonetheless, the effects of ischemia/reperfusion injury elicited by oxidative stress on cardiac fibroblast function associated with tissue repair are not completely understood. Ascorbic acid, deferoxamine, and N-acetylcysteine (A/D/N) are antioxidants with known cardioprotective effects, but the potential beneficial effects of combining these antioxidants in the tissue repair properties of cardiac fibroblasts remain unknown. Thus, the aim of this study was to evaluate whether the pharmacological association of these antioxidants, at low concentrations, could confer protection to cardiac fibroblasts against simulated ischemia/reperfusion injury. To test this, neonatal rat cardiac fibroblasts were subjected to simulated ischemia/reperfusion in the presence or absence of A/D/N treatment added at the beginning of simulated reperfusion. Cell viability was assessed using trypan blue staining, and intracellular reactive oxygen species (ROS) production was assessed using a 2′,7′-dichlorofluorescin diacetate probe. Cell death was measured by flow cytometry using propidium iodide. Cell signaling mechanisms, differentiation into myofibroblasts and pro-collagen I production were determined by Western blot, whereas migration was evaluated using the wound healing assay. Our results show that A/D/N association using a low concentration of each antioxidant increased cardiac fibroblast viability, but that their separate administration did not provide protection. In addition, A/D/N association attenuated oxidative stress triggered by simulated ischemia/reperfusion, induced phosphorylation of pro-survival extracellular-signal-regulated kinases 1/2 (ERK1/2) and PKB (protein kinase B)/Akt, and decreased phosphorylation of the pro-apoptotic proteins p38- mitogen-activated protein kinase (p38-MAPK) and c-Jun-N-terminal kinase (JNK). Moreover, treatment with A/D/N also reduced reperfusion-induced apoptosis, evidenced by a decrease in the sub-G1 population, lower fragmentation of pro-caspases 9 and 3, as well as increased B-cell lymphoma-extra large protein (Bcl-xL)/Bcl-2-associated X protein (Bax) ratio. Furthermore, simulated ischemia/reperfusion abolished serum-induced migration, TGF-β1 (transforming growth factor beta 1)-mediated cardiac fibroblast-to-cardiac myofibroblast differentiation, and angiotensin II-induced pro-collagen I synthesis, but these effects were prevented by treatment with A/D/N. In conclusion, this is the first study where a pharmacological combination of A/D/N, at low concentrations, protected cardiac fibroblast viability and function after simulated ischemia/reperfusion, and thereby represents a novel therapeutic approach for cardioprotection.