Miracle-dz/UniFAR-FTUs huggingface dataset:
Textile wastewater treatment efficiency by Fenton oxidation with integration of membrane separation system

Abstract This work investigates the performance of an integrated Fenton-Ultrafiltration treatment scheme to treat textile wastewater. The treated effluent is particle-free at a quality higher than that obtained by any novel membrane based process or Fenton oxidation in singularity. The study is divided into three parts: part one, Fenton process was optimized for COD: H2O2 (wt/wt), H2O2: Fe+2 (wt/wt) and pH to attain highest degradation removal and lowest sludge generation. The process efficiency was analyzed by considering COD, TOC and color removal as key parameters. Part two, the process was scaled up to 5 L and efficiency of integrated system was investigated under optimized conditions by using two different types of membranes at different operating pressures. Part three, the performance of membrane process was studied in terms of flux behavior and its recovery. The treated effluent has COD, TOC and color removal values of 48.0 mg/L, 1.2 mg/L and >99% respectively. These values are compliant to typical discharge environmental standards.
Normal and Osteoarthritic Human Synovial Fluid Regulation of Articular Cartilage Proteoglycan-4 Secretion: Role of O2 and TGF-β

Author(s): Brown, C. | Abstract: The ability of the TGF-β1 inhibitor LY2157299 to block the higher PRG4 secretion stimulated chondrocytes cultured in OA SF suggests that TGF-β1 is involved in the higher levels of PRG4 secretion seen in osteoarthritis. OA SF has been found to have higher PRG4 levels than NL SF (1). Thus, we concluded that the higher PRG4 secretion by chondrocytes incubated in OA SF was due to stimulation by TGF-β1 in the OA SF.
Fuzzy Rough C-Mean Based Unsupervised CNN Clustering for Large-Scale Image Data

Deep learning has been well-known for a couple of years, and it indicates incredible possibilities for unsupervised learning of representations with the clustering algorithm. The forms of Convolution Neural Networks (CNN) are now state-of-the-art for many recognition and clustering tasks. However, with the perpetual incrementation of digital images, there exist more and more redundant, irrelevant, and noisy samples which cause CNN running to gradually decrease, and its clustering accuracy decreases concurrently. To conquer these issues, we proposed an effective clustering method for a large-scale image dataset which combines CNN and a Fuzzy-Rough C-Mean (FRCM) clustering algorithm. The main idea is that first a high-level representation, learned by multi-layers of CNN with one clustering layer, produce the initial cluster center, then during training image clusters, and representations, are updating jointly. FRCM is utilized to update the cluster centers in the forward pass, while the parameters of proposed CNN are updated by the backward pass based on Stochastic Gradient Descent (SGD). The concept of the rough set of lower and boundary approximations deal with uncertainty, vagueness, and incompleteness in cluster definition, and fuzzy sets enable efficient handling of overlapping partitions in the noisy environment. The experiment results show that the proposed FRCM based unsupervised CNN clustering method is better than the standard K-Mean, Fuzzy C-Mean, FRCM and also other deep-learning-based clustering algorithms on large-scale image data.
To what extent are women free to choose where to give birth? How discourses of risk, blame and responsibility influence birth place decisions

Over the past 50 years, two things have changed for women giving birth in high- income nations; birth has become much safer, and now takes place in hospital rather than at home. The extent to which these phenomena are related is a source of ongoing debate, but concern about high intervention rates in hospitals, and financial pressures on health care systems, have led governments, clinicians and groups representing women to support a return to birth in ‘ alternative ’ settings such as midwife-led birth centres or at home, particularly for well women with healthy pregnancies. Despite this, most women still plan to give birth in high-technology hospital labour wards. In this article, we draw on a longitudinal narrative study of pregnant women at three maternity services in England between October 2009 and November 2010. Our findings indicate that for many women, hospital birth with access to medical care remained the default option. When women planned hospital birth, they often conceptualised birth as medically risky, and did not raise concerns about overuse of birth interventions; instead, these were considered an essential form of rescue from the uncertainties of birth. Those who planned birth in alternative settings also emphasised their intention, and obligation, to seek medical care if necessary. Using sociocultural theories of risk to focus our analysis, we argue that planning place of birth is mediated by cultural and historical associations between birth and safety, and further influenced by prominent contemporary narratives of risk, blame and the responsibility. We conclude that even with high-level support for ‘ alternative ’ settings for birth, these discourses constrain women ’ s decisions, and effectively limit opportunities for planning birth in settings other than hospital labour wards. Our contention is that a combination of cultural and social factors helps explain the continued high uptake of hospital obstetric unit birth, and that for this to change, birth in alternative settings would need to be positioned as a culturally normative and acceptable practice.
Operational Strategies and Comprehensive Evaluation of Menthol Based Deep Eutectic Solvent for the Extraction of Lower Alcohols from Aqueous Media

Deep Eutectic Solvents (DESs) are gaining more interest as low-cost extraction media. Looking at its vast opportunity, the current work explores the extraction of alcohols namely ethanol, 1-propanol, and 1-butanol from the aqueous phase using two novel hydrophobic DES at 303.15 K and 1 atm. The preparation of DES possess a common HBA (Hydrogen Bond Acceptor) with a HBD (Hydrogen Bond Donor such as organic acids i.e., lauric acid and decanoic acid) at a certain proportion. Ratios of 2:1 and 1:1 were used for synthesizing menthol: lauric acid (DES-1) and menthol/decanoic acid (DES-2), respectively. The highest extraction efficiency of alcohols was observed in the presence of DES-1. Thereafter, atomistic molecular dynamics (MD) simulations have also been adopted to understand the extraction mechanism of alcohols from water using these DES. From MD simulations, the interaction energies, structural properties such as radial and special distribution functions, and dynamic properties such as self-diffusivity are.
Parametrization of particle coating process with chitosan in spouted bed

Abstract This research aimed to evaluate the main process variables effect on the coating of inert particles in spouted bed with a solution based on chitosan, and later to apply them in batch tests of anthocyanins adsorption extracted from red cabbage. For this, experimental design techniques were used to evaluate the impact of the inlet air temperature (T), spouting air relative flow (WREL) and the flow rate of the coating suspension (QCS) on the process efficiency response (η). The coating experiments were conducted for a total time of 40 min and a spray pressure of 0.1 MPa. From the results obtained, the best condition for executing the recoating process was determined, with inlet air temperature of 70 °C, relative flow of spouting air of 1.7 and 4 for flow coating suspension. This operational condition enabled process efficiencies close to 90%. The coating quality was analyzed by scanning electron microscopy (SEM) and the surface elemental composition was verified by X-ray energy dispersion spectroscopy (EDS). The process of coating inert particles with chitosan in the spouted bed provided satisfactory results, both from the point of view of process performance and in coated particle adsorption capacity.
International Journal of Instruction

Professional development (PD) has been widely implemented to shift mathematics instruction practices from teacher-centered (traditional practice) to studentcentered. As such, a study examining mediating factors on the relationship between PD and student-centered instruction is of great importance in enhancing the effectiveness of PD and shifting teacher practice. Although studies examining the mediating effects of contextual factors (e.g., administrative support) on the relationship between PD and instruction abound, studies exploring the effects of teachers’ psychological factors on this relationship are relatively scarce. In this study, we examined the mediating effects of mathematics teachers’ self-efficacy beliefs and classroom stress on the relationship between PD and student-centered instruction. We used a secondary data set collected for the 2015 Trends in International Mathematics and Science Study (TIMSS). For this data set, 317 teachers of eighth-grade mathematics, selected from 150 schools in Korea, were surveyed, and an analysis was conducted using structural equation modeling. Our findings revealed significant mediating effects of self-efficacy beliefs on the relationship between PD and student-centered instruction. However, the mediating effects of classroom stress were not significant. Moreover, we found significantly positive direct effects of PD and self-efficacy on student-centered instruction.
Sleep quality and depressive disorders among priests of the Archdiocese of Katowice

Przewlekły stres wpływa na jakość snu oraz wywołuje symptomy depresji u osób aktywnych zawodowo. Posługa kapłańska, ze względu na swą specyfikę, może generować przewlekły stres, wpływać na jakość snu i wywoływać depresję. Celem pracy jest analiza obciążeń zawodowych księży katolickich, ocena jakości snu i rozpowszechnienia zaburzeń depresyjnych w tej grupie oraz wyodrębnienie czynników mających wpływ na ich występowanie u duchownych.Zbadano 223 księży diecezjalnych i zakonnych Archidiecezji Katowickiej. W badaniu zastosowano autorski, poddany walidacji kwestionariusz, skalę depresji Becka (Beck Depression Inventory – BDI-II) oraz Skalę Jakości Snu (SJS). Czynnikami wywołującymi najsilniejszy stres u badanych księży były relacje z przełożonymi (68,2%) oraz zmiana parafii (66,8%). Najczęstszym z subiektywnie odczuwanych przez respondentów negatywnych stanów podczas całej dotychczasowej służby kapłańskiej było przemęczenie (92,4%). W badanej grupie u 20,2% księży występowała pogorszona jakość snu, a zaburzenia depresyjne o różnym stopniu nasilenia wykazano u 27,4% badanych. Wykazano zależność jakości snu oraz depresji od nasilenia stresu związanego ze zmianą parafii, relacjami z przełożonymi, celibatem oraz życiem w pojedynkę. Księża niechętnie poddają się badaniu kwestionariuszowemu dotyczącemu stanu zdrowia psychicznego, jednocześnie stanowią grupę wysokiego ryzyka występowania zaburzeń snu i zaburzeń depresyjnych. Im niższa była jakość snu, tym wyższe wskaźniki zaburzeń depresyjnych. Perfekcjonizm, nadmierne zaangażowanie, poczucie niezrozumienia, potrzeba uznania i wysoka wrażliwość interpersonalna sprzyjały nasileniu symptomów depresji w badanej grupie.
Experimental and Theoretical Investigations of Terahertz Spectra of the Structural Isomers: Mannose and Galactose

The high-resolution terahertz spectra of the two structural isomers, mannose and galactose, have been measured by terahertz time-domain spectroscopy (THz-TDS) in the range of 0.5–4.0 THz at room temperature. Significant differences between these similar molecules have been found in their THz characteristic spectra, implying that THz-TDS is a powerful tool for identifying isomers. Structural analyses and normal mode calculations of the two systems were performed using solid-state density functional theory (DFT) with the PBE and PW91 density functionals as well as using gas-state DFT with B3LYP hybrid functional. Among these calculations, the solid-state simulated results obtained from the PBE method exhibit a good agreement with the experimentally measured spectra. According to the calculated results of PBE, the observed spectral features were assigned as primarily external lattice translations, deformations, and rotations with lesser contributions due to intramolecular motion of pyranose ring, CH2OH group, and hydroxyl groups.
The Use of ICT by Local General Administrative Authorities during COVID-19 for a Sustainable Future: Comparing Five European Countries

The COVID-19 pandemic has significantly reshaped administrative relations and put emphasis on the digital transformation of public administration that is urgently needed to support a sustainable recovery from the pandemic crisis and future sustainable development in the post-pandemic era. This paper presents a comparative study on the ways the first wave of the COVID-19 pandemic impacted general administrative authorities on the local level with respect to various aspects of their functioning and digitalization in five European countries. With a sample of 926 respondents from the Czech Republic, Germany, Poland, Romania, and Slovenia, the study shows that the pandemic-imposed changes are very similar in these countries. The results reveal that, except for Germany, the biggest problems of pandemic-related regulations are their obscurity. For all countries under study, parties to the procedures are shown to be the main driver of digitalization and not the public administration itself, generally lagging behind in this sense. Nevertheless, the pandemic has also created several potential opportunities, whereby public managers, especially in Germany, have acknowledged the importance of digitalization right after the protection of health, as confirmed by the wider use of ICT equipment, particularly in Germany and the Czech Republic. Moreover, Germany and Romania exhibit the greatest potential to accelerate digitalization. Finally, the critical factors influencing accelerated digitalization after the pandemic are also identified. The paper’s evidence-based findings could prove useful while formulating recommendations for the sustainable practices of public administrations during this and any future pandemic crisis.
Improving the accuracy and reliability of temperature field simulation during laser metal deposition

ABSTRACT Laser metal deposition (LMD), as a major metal additive manufacturing (AM) process, features complex thermal history. The local temperature field, which varies with location and time, plays a vital role in affecting the microstructure and mechanical properties of the final product. This study develops a robust numerical model based on finite element analysis (FEA) to determine the temperature field in an accurate and reliable way. Taking a titanium alloy as an example, the melt pool geometry is used to select the best heat source model and key thermal parameters. Temperature measurements underneath the melt pool using thermocouples are employed to quantify the location-dependent heat convection model by comparing the thermal history. Some strategies for further refinement of this numerical model are also discussed in this paper. This improved numerical model is expected to provide a solid ground to support reliable simulation of microstructure and mechanical properties for the LMD process.
Development of Toolkit for Formalizing the Programming of Canned Cycles on CNC Machine Tools

The analysis shows that the development of programming tools for CNC systems is focused on the development of new machine canned cycles, including those for processing complicated surfaces, their complex combinations or complex mutual arrangement, but does not concern such issues as the universalization of cycle parameters. This does not make it impossible to transfer control programs from one CNC system to another. This work proposes an approach to the development of tools for creating universal cycles of typical technological transitions of machining on machines with different CNC systems.
The Renewable Energy (RE) Industry Workforce Needs: RE Simulation and Analysis Tools Teaching as an Effective Way to Enhance Undergraduate Engineering Students’ Learning

The share of renewables in the U.S. electricity generation mix is increasing and one of the major obstacles to enhancing employment in the renewable energy (RE) sector is finding skilled/qualified labor to fill positions. RE systems engineer jobs mostly need bachelor’s degrees but there are few RE engineering-focused degree programs. Therefore, there are needs to accurately train undergraduate engineering students at universities and match the education system offerings to meet RE industry demands. This study reviews RE employment by technology, RE industry workforce needs, and engineering programs accreditation, and then suggests possible means, along with theoretical RE concepts, to enhance undergraduate engineering students’ RE learning at universities. In particular, RE industries require technology skills, including analytical, scientific, and simulation software programs or tools. These RE simulation and analysis tools can be used for teaching, training, techno-economic analysis, planning, designing, optimization, etc., and are the focus of this review.
Measured and predicted freeze-thaw days frequencies in climate change conditions in central Poland

The rate of progression of geomorphological phenomena is greatly influenced by freeze-thaw processes. In the face of air temperature increasing over the past few decades, a question of the future impact of these processes arises, notably in the temperate and cold climate zones. Using the mean, maximum and minimum daily air temperature data in the period 1951–2018 obtained from three weather stations located in the vicinity of Jeziorsko reservoir (central Poland), we have determined the mathematical correlation, described with a polynomial function, between the mean monthly air temperature and the monthly number of freeze-thaw days (FTD). A freeze-thaw day is a day when the maximum air temperature is above 0 °C while the minimum air temperature equals or is below this threshold. The number of FTDs within the study area averaged 64–71 and demonstrated a downward trend of 2–4 FTDs/10 years. The study period (1951–2018), includes a clearly marked distinct sub-period (1991–2018), when the reservoir was in operation, which experienced 58–68 FTDs. Considering the assumed rise in temperature, one should expect a further, though slightly slower, decline in the future number of FTDs. Depending on the accepted model of the temperature increase, which for the area of Poland (Central Europe) in the perspective of 30 years oscillates between +1.1 to +1.3 °C, the number of FTDs within the study area is expected to decline by −4.5 to −5.3 FTD, i.e. 6–7% and 5.4–5.5 FTD i.e. 8–9% respectively.
Predictive UAV Base Station Deployment and Service Offloading With Distributed Edge Learning

In modern networks, edge computing will be responsible for processing and learning from the critical network- and user-generated data, such as wireless link usage, mobility information, application requests, and many others. The presence of Artificial Intelligence-based (AI) applications at the edge of the network will enable the network to predict necessary user behavior and its impact on network infrastructure, such as base station overloading. One of the main strategies for offloading users and base stations is to deploy UAV base stations, or flying base stations, which can dynamically provide service and connectivity. In this article, we introduce a framework for distributed learning over Multi-access Edge Computing (MEC), which manages data applications in a fully distributed setting across edge servers, thus reducing the cost of collecting user information in a centralized server. We couple the proposed distributed learning with a novel similarity metric for user trajectories, which can aggregate neural network models with similar costs as other model aggregation techniques. However, the aggregation technique can achieve much higher accuracy. Furthermore, we apply the proposed distributed learning scheme to manage and deploy flying base stations to areas that experience high demand or poor user connectivity, thus optimizing connectivity in terms of user satisfaction, delay, and network throughput.
Increasing the Performance of a Fiber-Reinforced Concrete for Protective Facilities

The use of fiber in cement materials is a promising and effective replacement for bar reinforcement. A wide range of fiber-reinforced concretes based on composite binders with increased impact strength characteristics have been developed. The synthesized composites included the composite binder made of Portland cement, silica, and carbonate additives. Basalt and steel were used as fibers. The nature of the influence of the composition and manufacturing technology of cement composites on the dynamic hardening coefficient has been established, while the growth of these indicators is achieved by creating a denser interfacial transition zone between the cement paste, aggregate, and fiber as a result of improving the homogeneity of the concrete mixture and controlling the consistency. Workability indicators (slump flow up to 730 mm; spreading time up to a diameter of 50 cm is up to 3 s) allow them to be classified as self-compacting concrete mixtures. An increase in the values of the impact strength coefficient by a factor of 5.5, the dynamic hardening coefficient by almost 70% as a result of interfacial interaction between fibers and binder matrix in the concrete composite, as well as absorption of impact energy by fiber, was revealed. The formula describing the effect of the loading rate on the coefficient of dynamic hardening of fiber-reinforced concrete has been refined. The fracture processes of the obtained materials have been established: after the initiation of primary cracks, the structure of the composite absorbs impact energy for a long time, while in the inelastic range (the onset of cracking and peak loads), a large number of secondary cracks appear.