bluuebunny/crossref_metadata_2025 huggingface dataset:
Communicating Threats and Potential Opportunities to Reduce Microplastic Pollution with Key Stakeholders
Authors: Walker Tony R.
Published: June 2022

Plastic pollution has attracted considerable media attention from the public, governments, and industry in the past decade resulting in increased awareness of the direct environmental, economic and human health impacts [...]
Accelerating Global Sensitivity Analysis via Supervised Machine Learning Tools: Case Studies for Mineral Processing Models
Authors: Lucay Freddy A.
Published: June 2022

Global sensitivity analysis (GSA) is a fundamental tool for identifying input variables that determine the behavior of the mathematical models under uncertainty. Among the methods proposed to perform GSA, those based on the Sobol method are highlighted because of their versatility and robustness; however, applications using complex models are impractical owing to their significant processing time. This research proposes a methodology to accelerate GSA via surrogate models based on the modern design of experiments and supervised machine learning (SML) tools. Three case studies based on an SAG mill and cell bank are presented to illustrate the applicability of the proposed procedure. The first two consider batch training for SML tools included in the Python and R programming languages, and the third considers online sequential (OS) training for an extreme learning machine (ELM). The results reveal significant computational gains from the methodology proposed. In addition, GSA enables the quantification of the impact of critical input variables on metallurgical process performance, such as ore hardness, ore size, and superficial air velocity, which has only been reported in the literature from an experimental standpoint. Finally, GSA-OS-ELM opens the door to estimating online sensitivity indices for the equipment used in mineral processing.
Effects of Charged Solute-Solvent Interaction on Reservoir Temperature during Subsurface CO2 Injection
Authors: Paolini Christopher
Published: June 2022

A short-term side-effect of CO2 injection is a developing low-pH front that forms ahead of the bulk water injectant, due to differences in solute diffusivity. Observations of downhole well temperature show a reduction in aqueous-phase temperature with the arrival of a low-pH front, followed by a gradual rise in temperature upon the arrival of a high concentration of bicarbonate ion. In this work, we model aqueous-phase transient heat advection and diffusion, with the volumetric energy generation rate computed from solute-solvent interaction using the Helgeson–Kirkham–Flowers (HKF) model, which is based on the Born Solvation model, for computing specific molar heat capacity and the enthalpy of charged electrolytes. A computed injectant water temperature profile is shown to agree with the actual bottom hole sampled temperature acquired from sensors. The modeling of aqueous-phase temperature during subsurface injection simulation is important for the accurate modeling of mineral dissolution and precipitation because forward dissolution rates are governed by a temperature-dependent Arrhenius model.
Competing Metal–Ligand Interactions in Tris(cyclopentadienyl)-cyclohexylisonitrile Complexes of Trivalent Actinides and Lanthanides
Authors: Kovács Attila , Apostolidis Christos , Walter Olaf
Published: June 2022

The structure and bonding properties of 16 complexes formed by trivalent f elements (M=U, Np, Pu and lanthanides except for Pm and Pr) with cyclopentadienyl (Cp) and cyclohexylisonitrile (C≡NCy) ligands, (Cp)3M(C≡NCy), were studied by a joint experimental (XRD, NMR) and theoretical (DFT) analysis. For the large La(III) ion, the bis-adduct (Cp)3La(C≡NCy)2 could also be synthesized and characterized. The metal–ligand interactions, focusing on the comparison of the actinides and lanthanides as well as on the competition of the two different ligands for M, were elucidated using the Quantum Theory of Atoms in Molecules (QTAIM) and Natural Bond Orbital (NBO) models. The results point to interactions of comparable strengths with the anionic Cp and neutral C≡NCy ligands in the complexes. The structural and bonding properties of the actinide complexes reflect small but characteristic differences with respect to the lanthanide analogues. They include larger ligand-to-metal charge transfers as well as metal–ligand electron-sharing interactions. The most significant experimental marker of these covalent interactions is the C≡N stretching frequency.
Effects of Anthraquinones on Immune Responses and Inflammatory Diseases
Authors: Xin Dandan , Li Huhu , Zhou Shiyue , Zhong Hao , Pu Weiling
Published: June 2022

The anthraquinones (AQs) and derivatives are widely distributed in nature, including plants, fungi, and insects, with effects of anti-inflammation and anti-oxidation, antibacterial and antiviral, anti-osteoporosis, anti-tumor, etc. Inflammation, including acute and chronic, is a comprehensive response to foreign pathogens under a variety of physiological and pathological processes. AQs could attenuate symptoms and tissue damages through anti-inflammatory or immuno-modulatory effects. The review aims to provide a scientific summary of AQs on immune responses under different pathological conditions, such as digestive diseases, respiratory diseases, central nervous system diseases, etc. It is hoped that the present paper will provide ideas for future studies of the immuno-regulatory effect of AQs and the therapeutic potential for drug development and clinical use of AQs and derivatives.
Synthesis, Characterization, DFT and Photocatalytic Studies of a New Pyrazine Cadmium(II) Tetrakis(4-methoxy-phenyl)-porphyrin Compound
Authors: Mchiri Chadlia , Coetzee Louis-Charl C. , Chandoul Faycal , Jedidi Abdesslem , Adeyinka Adedapo S. , Magwa Nomampondo , Roisnel Thierry , Ben Moussa Sana , Nasri Habib
Published: June 2022

This study describes the synthesis, theoretical investigations, and photocatalytic degradational properties of a new (pyrazine)(meso-tetrakis(4-tert-methoxyphenyl)-porphyrinato)-cadmium (II) ([Cd(TMPP)-Pyz]) complex (1). The new penta-coordinated CdII porphyrin complex (1) was characterized by various spectroscopic techniques, including FT-IR, NMR, UV-visible absorption, fluorescence emission, and singlet oxygen, while its molecular structure was studied using single crystal X-ray diffraction. The UV–Vis spectroscopic study highlighted the redshift of the absorption bands after the insertion of the Cd(II) metal ion into the TMPP ring. The co-coordination of the pyrazine axial ligand enhanced this effect. A fluorescence emission spectroscopic study showed a significant blueshift in the Q bands, accompanied by a decrease in the fluorescence emission intensity and quantum yields of Φf = 0.084, Φf = 0.06 and Φf = 0.03 for H2-TMPP free-base porphyrin, [Cd(TMPP)] and [Cd(TMPP)(Pyz)] (1) respectively. Singlet oxygen revealed that the H2-TMPP porphyrin produced the most efficient singlet oxygen quantum yield of (ΦΔ = 0.73) compared to [CdTMPP] (ΦΔ = 0.57) and [Cd(TMPP)(Pyz)] (1) (ΦΔ = 0.13). In the crystal lattice, the [Cd(TMPP)Pyz] was stabilized through non-covalent intermolecular interactions (NCI), such as the hydrogen bonds C-H···N and C-H···Cg. Additionally, crystal explorer software was then utilized to measure the quantitative analysis of the intermolecular interactions in the unit cell of the crystal structure and established that the C-H···π interaction dominated. The Natural bond orbital (NBO) analysis revealed that each molecule is stabilized by hyperconjugation and charge delocalization. As a photocatalyst, the coordination complex 1 showed excellent photocatalytic activity toward the degradation of Levafix Blue CA reactive dye (i.e., dye photo-degradation of 80%).
A Review of Cobalt-Containing Nanomaterials, Carbon Nanomaterials and Their Composites in Preparation Methods and Application
Authors: Chen Hongfeng , Wang Wei , Yang Lin , Dong Liang , Wang Dechen , Xu Xinkai , Wang Dijia , Huang Jingchun , Lv Mengge , Wang Haiwang
Published: June 2022

With the increasing demand for sustainable and green energy, electric energy storage technologies have received enough attention and extensive research. Among them, Li-ion batteries (LIBs) are widely used because of their excellent performance, but in practical applications, the electrochemical performance of electrode materials is not satisfactory. Carbon-based materials with high chemical stability, strong conductivity, high specific surface area, and good capacity retention are traditional anode materials in electrochemical energy storage devices, while cobalt-based nano-materials have been widely used in LIBs anodes because of their high theoretical specific capacity. This paper gives a systematic summary of the state of research of cobalt-containing nanomaterials, carbon nanomaterials, and their composites in LIBs anodes. Moreover, the preparation methods of electrode materials and measures to improve electrochemical performance are also summarized. The electrochemical performance of anode materials can be significantly improved by compounding carbon nanomaterials with cobalt nanomaterials. Composite materials have better electrical conductivity, as well as higher cycle ability and reversibility than single materials, and the synergistic effect between them can explain this phenomenon. In addition, the electrochemical performance of materials can be significantly improved by adjusting the microstructure of materials (especially preparing them into porous structures). Among the different microscopic morphologies of materials, porous structure can provide more positions for chimerism of lithium ions, shorten the diffusion distance between electrons and ions, and thus promote the transfer of lithium ions and the diffusion of electrolytes.
Dietary Bioactives: Their Role in the Prevention and Treatment of Cardiovascular and Metabolic Bone Diseases
Authors: Mandatori Domitilla , Pandolfi Assunta
Published: June 2022

Cardiovascular and metabolic bone diseases are demanding health problems with high morbidity and mortality [...]
Adherence to Lifestyle Recommendations for Bone Health in Older Adults with and without Osteoporosis: Cross-Sectional Results of the OUTDOOR ACTIVE Study
Authors: Albrecht Birte Marie , Stalling Imke , Foettinger Linda , Recke Carina , Bammann Karin
Published: June 2022

Sustaining good bone health into older age is key for preventing osteoporosis. Bone health is associated with several lifestyle factors. This study investigates older adults’ adherence to bone health-promoting lifestyle recommendations dependent on osteoporosis status. Cross-sectional data of 1610 community-dwelling older adults (65–75 years) residing in Bremen, Germany (53.4% female) were included. The Osteoporosis Self-Assessment Tool and self-reported osteoporosis diagnosis were used to classify participants by osteoporosis status (low risk, high risk, diagnosis). Adherence to bone health recommendations regarding calcium and vitamin D intake, sun exposure, alcohol consumption, resistance/weight-bearing exercise, and physical activity were assessed. Descriptive statistics were applied, stratified by sex and osteoporosis status. A total of 91 women (10.6%) and 15 men (2.0%) reported an osteoporosis diagnosis, 457 women (43.2%) and 311 men (41.4%) were classified as having a high risk, and 311 women (36.2%) and 425 men (56.6%) as having a low risk. Adherence to bone health recommendations was high for calcium intake (93.3–100.0%), vitamin D intake (77.8–93.3%), and sun exposure (86.7–97.7%). Lower adherence was observed regarding resistance/weight-bearing exercise (36.3–54.4%), physical activity (14.3–57.7%), and alcohol consumption (40.0–72.4%). In conclusion, tailored prevention strategies are needed that focus on older adults with an osteoporosis diagnosis or who are at high risk.
Risk of Chronic Disease after an Episode of Marasmus, Kwashiorkor or Mixed–Type Severe Acute Malnutrition in the Democratic Republic of Congo: The Lwiro Follow-Up Study
Authors: Mwene-Batu Pacifique , Bisimwa Ghislain , Donnen Philippe , Bisimwa Jocelyne , Tshongo Christian , Dramaix Michelle , Hermans Michel P. , Briend André
Published: June 2022

Background: Long-term impact of different forms of severe acute malnutrition (SAM) in childhood on the emergence of noncommunicable diseases (NCDs) is poorly known. Aim: To explore the association between subtypes of SAM during childhood, NCDs, and cardiovascular risk factors (CVRFs) in young adults 11 to 30 years after post-SAM nutritional rehabilitation. Methods: In this follow-up study, we investigated 524 adults (mean age 22 years) treated for SAM during childhood in eastern Democratic Republic of the Congo (DRC) between 1988 and 2007. Among them, 142 had a history of marasmus, 175 of kwashiorkor, and 207 had mixed-form SAM. These participants were compared to 407 aged- and sex-matched control adults living in the same community without a history of SAM. Our outcomes of interest were cardiometabolic risk markers for NCDs. Logistic and linear regressions models were sued to estimate the association between subtype of SAM in childhood and risk of NCDs. Results: Compared to unexposed, former mixed-type SAM participants had a higher adjusted ORs of metabolic syndrome [2.68 (1.18; 8.07)], central obesity [1.89 (1.11; 3.21)] and low HDL-C (High-density lipoprotein cholesterol) [1.52 (1.08; 2.62)]. However, there was no difference between groups in terms of diabetes, high blood pressure, elevated LDL-C (low-density lipoprotein cholesterol) and hyper TG (hypertriglyceridemia) and overweightness. Former mixed-type SAM participants had higher mean fasting glucose [3.38 mg/dL (0.92; 7.7)], reduced muscle strength [−3.47 kg (−5.82; −1.11)] and smaller hip circumference [−2.27 cm (−4.24; −0.31)] compared to non-exposed. Regardless of subtypes, SAM-exposed participants had higher HbA1c than unexposed (p < 0.001). Those with a history of kwashiorkor had cardiometabolic and nutritional parameters almost superimposable to those of unexposed. Conclusion: The association between childhood SAM, prevalence of NCDs and their CVRFs in adulthood varies according to SAM subtypes, those with mixed form being most at risk. Multicenter studies on larger cohorts of older participants are needed to elucidate the impact of SAM subtypes on NCDs risk.
Synthesis of Amino-Acid-Based Nitroalkenes
Authors: Gerogianni Velisaria-Eleni , Koutoulogenis Giorgos S. , Gerokonstantis Dimitrios Triantafyllos , Kokotos George
Published: June 2022

Fatty-acid-based nitroalkenes have recently received great attention because of their bioactivities. On the contrary, peptide- or amino-acid-based nitroalkenes have been scarcely explored so far, although they may exhibit interesting biological properties, for example, as enzyme inhibitors. In this work, we study protocols for the efficient synthesis of nitroalkenes based on natural amino acids. A variety of N-protected amino alcohols and Weinreb amides, derived from α-amino acids, were converted to the corresponding N-protected amino aldehydes, and, through a Henry reaction with nitroalkanes, produced the corresponding nitro alcohols. The subsequent elimination reaction led to the (E)-isomer of amino-acid-based nitroalkenes in moderate to high yields.
Mechanistic Analysis of Chemically Diverse Bromodomain-4 Inhibitors Using Balanced QSAR Analysis and Supported by X-ray Resolved Crystal Structures
Authors: Zaki Magdi E. A. , Al-Hussain Sami A. , Al-Mutairi Aamal A. , Masand Vijay H. , Samad Abdul , Jawarkar Rahul D.
Published: June 2022

Bromodomain-4 (BRD-4) is a key enzyme in post-translational modifications, transcriptional activation, and many other cellular processes. Its inhibitors find their therapeutic usage in cancer, acute heart failure, and inflammation to name a few. In the present study, a dataset of 980 molecules with a significant diversity of structural scaffolds and composition was selected to develop a balanced QSAR model possessing high predictive capability and mechanistic interpretation. The model was built as per the OECD (Organisation for Economic Co-operation and Development) guidelines and fulfills the endorsed threshold values for different validation parameters (R2tr = 0.76, Q2LMO = 0.76, and R2ex = 0.76). The present QSAR analysis identified that anti-BRD-4 activity is associated with structural characters such as the presence of saturated carbocyclic rings, the occurrence of carbon atoms near the center of mass of a molecule, and a specific combination of planer or aromatic nitrogen with ring carbon, donor, and acceptor atoms. The outcomes of the present analysis are also supported by X-ray-resolved crystal structures of compounds with BRD-4. Thus, the QSAR model effectively captured salient as well as unreported hidden pharmacophoric features. Therefore, the present study successfully identified valuable novel pharmacophoric features, which could be beneficial for the future optimization of lead/hit compounds for anti-BRD-4 activity.
Clinical Efficacy of Carbocysteine in COPD: Beyond the Mucolytic Action
Authors: Pace Elisabetta , Cerveri Isa , Lacedonia Donato , Paone Gregorino , Sanduzzi Zamparelli Alessandro , Sorbo Rossella , Allegretti Marcello , Lanata Luigi , Scaglione Francesco
Published: June 2022

Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease with a versatile and complicated profile, being the fourth most common single cause of death worldwide. Several research groups have been trying to identify possible therapeutic approaches to treat COPD, such as the use of mucoactive drugs, which include carbocysteine. However, their role in the treatment of patients suffering from COPD remains controversial due to COPD’s multifaceted profile. In the present review, 72 articles, published in peer-reviewed journals with high impact factors, are analyzed in order to provide significant insight and increase the knowledge about COPD considering the important contribution of carbocysteine in reducing exacerbations via multiple mechanisms. Carbocysteine is in fact able to modulate mucins and ciliary functions, and to counteract viral and bacterial infections as well as oxidative stress, offering cytoprotective effects. Furthermore, carbocysteine improves steroid responsiveness and exerts anti-inflammatory activity. This analysis demonstrates that the use of carbocysteine in COPD patients represents a well-tolerated treatment with a favorable safety profile, and might contribute to a better quality of life for patients suffering from this serious illness.
Effectiveness and Nephrotoxicity of Loading Dose Colistin–Meropenem versus Loading Dose Colistin–Imipenem in the Treatment of Carbapenem-Resistant Acinetobacter baumannii Infection
Authors: Katip Wasan , Oberdorfer Peninnah , Kasatpibal Nongyao
Published: June 2022

Carbapenem-resistant Acinetobacter baumannii (CRAB) is becoming more widely recognized as a serious cause of nosocomial infections, and colistin has been reintroduced in recent years for the treatment of CRAB infection. Combinations of colistin and meropenem or imipenem have been found to be effective against CRAB isolates, whereas clinical investigations have not definitively demonstrated the theoretical benefits of colistin combined therapy in patients with CRAB infections. The objective of this study was to compare the primary outcome (30-day survival rate) and secondary outcomes (clinical response, microbiological response and nephrotoxicity) between patients who received loading dose (LD) colistin–meropenem and LD colistin–imipenem for the treatment of CRAB infection. A retrospective cohort analysis was performed at Chiang Mai University Hospital in patients with CRAB infection who received LD colistin–meropenem or LD colistin–imipenem between 2011 and 2017, and 379 patients fulfilled the requirements for the inclusion criteria. The results of this study showed that patients who received LD colistin–imipenem had a lower 30-day survival rate (adjusted HR = 0.57, 95% CI: 0.37–0.90; p = 0.015) and a lower clinical response (aHR = 0.56, 95% CI: 0.35–0.90; p = 0.017) compared with those who received LD colistin–meropenem. The microbiological response in patients with LD colistin–imipenem was 0.52 times (aHR) lower than that in those who received colistin–meropenem (95% CI: 0.34–0.81; p = 0.004); however, there was no significant difference in nephrotoxicity (aHR = 1.03, 95% CI: 0.67–1.57; p = 0.897) between the two combination regimens. In conclusion, when comparing the combination of LD colistin with imipenem or meropenem, the combination of LD colistin and meropenem provides a better survival rate for treating CRAB. Thus, we suggest that combinations of LD colistin and meropenem should be considered when treating CRAB infections.
Hyaluronan Hydrogels: Rheology and Stability in Relation to the Type/Level of Biopolymer Chemical Modification
Authors: La Gatta Annalisa , Bedini Emiliano , Aschettino Maria , Finamore Rosario , Schiraldi Chiara
Published: June 2022

BDDE (1,4-butanediol-diglycidylether)-crosslinked hyaluronan (HA) hydrogels are widely used for dermo-aesthetic purposes. The rheology and stability of the gels under physiological conditions greatly affect their clinical indications and outcomes. To date, no studies investigating how these features are related to the chemistry of the polymeric network have been reported. Here, four available HA-BDDE hydrogels were studied to determine how and to what extent their rheology and stability with respect to enzymatic hydrolysis relate to the type and degree of HA structural modification. 1H-/13C-NMR analyses were associated for the quantification of the “true” HA chemical derivatization level, discriminating between HA that was effectively crosslinked by BDDE, and branched HA with BDDE that was anchored on one side. The rheology was measured conventionally and during hydration in a physiological medium. Sensitivity to bovine testicular hyaluronidase was quantified. The correlation between NMR data and gel rheology/stability was evaluated. The study indicated that (1) the gels greatly differed in the amounts of branched, crosslinked, and overall modified HA, with most of the HA being branched; (2) unexpectedly, the conventionally measured rheological properties did not correlate with the chemical data; (3) the gels’ ranking in terms of rheology was greatly affected by hydration; (4) the rheology of the hydrated gels was quantitatively correlated with the amount of crosslinked HA, whereas the correlations with the total HA modification level and with the degree of branched HA were less significant; (5) increasing HA derivatization/crosslinking over 9/3 mol% did not enhance the stability with respect to hyaluronidases. These results broaden our knowledge of these gels and provide valuable information for improving their design and characterization.
Complexation in Aqueous Solution of a Hydrophobic Polyanion (PSSNa) Bearing Different Charge Densities with a Hydrophilic Polycation (PDADMAC)
Authors: Jemili Nouha , Fauquignon Martin , Grau Etienne , Fatin-Rouge Nicolas , Dole François , Chapel Jean-Paul , Essafi Wafa , Schatz Christophe
Published: June 2022

In this work the electrostatic complexation of two strong polyelectrolytes (PEs) was studied, the hydrophilic and positively charged poly (diallyldimethylammonium chloride) (PDADMAC) and the hydrophobic and negatively charged poly (styrene-co-sodium styrene sulfonate) (P(St-co-SSNa)), which was prepared at different sulfonation rates. The latter is known to adopt a pearl necklace conformation in solution for intermediate sulfonation rates, suggesting that a fraction of the P(St-co-SSNa) charges might be trapped in these hydrophobic domains; thus making them unavailable for complexation. The set of complementary techniques (DLS, zetametry, ITC, binding experiment with a cationic and metachromatic dye) used in this work highlighted that this was not the case and that all anionic charges of P(St-co-SSNa) were in fact available for complexation either with the polycationic PDADMAC or the monocationic o-toluidine blue dye. Only minor differences were observed between these techniques, consistently showing a complexation stoichiometry close to 1:1 at the charge equivalence for the different P(St-co-SSNa) compositions. A key result emphasizing that (i) the strength of the electrostatic interaction overcomes the hydrophobic effect responsible for pearl formation, and (ii) the efficiency of complexation does not depend significantly on differences in charge density between PDADMAC and P(St-co-SSNa), highlighting that PE chains can undergo conformational rearrangements favoring the juxtaposition of segments of opposite charge. Finally, these data have shown that the formation of colloidal PECs, such as PDADMAC and P(St-co-SSNa), occurs in two distinct steps with the formation of small primary complex particles (<50 nm) by pairing of opposite charges (exothermic step) followed by their aggregation within finite-size clusters (endothermic step). This observation is in agreement with the previously described mechanism of PEC particle formation from strongly interacting systems containing a hydrophobic PE.
Environmental Stress Cracking of High-Density Polyethylene Applying Linear Elastic Fracture Mechanics
Authors: Thuy Maximilian , Pedragosa-Rincón Miquel , Niebergall Ute , Oehler Harald , Alig Ingo , Böhning Martin
Published: June 2022

The crack propagation rate of environmental stress cracking was studied on high-density polyethylene compact tension specimens under static loading. Selected environmental liquids are distilled water, 2 wt% aqueous Arkopal N100 solution, and two model liquid mixtures, one based on solvents and one on detergents, representing stress cracking test liquids for commercial crop protection products. The different surface tensions and solubilities, which affect the energetic facilitation of void nucleation and craze development, are studied. Crack growth in surface-active media is strongly accelerated as the solvents induce plasticization, followed by strong blunting significantly retarding both crack initiation and crack propagation. The crack propagation rate for static load as a function of the stress intensity factor within all environments is found to follow the Paris–Erdogan law. Scanning electron micrographs of the fracture surface highlight more pronounced structures with both extensive degrees of plasticization and reduced crack propagation rate, addressing the distinct creep behavior of fibrils. Additionally, the limitations of linear elastic fracture mechanisms for visco-elastic polymers exposed to environmental liquids are discussed.
Experimental Investigation of Shale Tensile Failure under Thermally Conditioned Linear Fracturing Fluid (LFF) System and Reservoir Temperature Controlled Conditions
Authors: Iferobia Cajetan Chimezie , Ahmad Maqsood , Ali Imtiaz
Published: June 2022

Linear fracturing fluid (LFF) provides viscosity driven benefits of proppant suspensibility and fluid loss control, and with the use of a breaker agent, flowback recovery can be greatly enhanced. Shale tensile strength is critical in the prediction of fracture initiation and propagation, but its behavior under the interaction with LFF at reservoir temperature conditions remains poorly understood. This necessitated an in-depth investigation into the tensile strengths of Eagle Ford and Wolfcamp shales under thermally conditioned LFF and reservoir temperature controlled conditions. Brazilian Indirect Tensile Strength (BITS) testing was carried out for the quantitative evaluation of shale tensile strength, followed by extensive failure pattern classifications and surface crack length analysis. The thermally conditioned LFF saturation of shale samples led to average tensile strength (ATS) increases ranging from 26.33–51.33% for Wolfcamp. Then, for the Eagle Ford samples, ATS increases of 3.94 and 6.79% and decreases of 3.13 and 15.35% were recorded. The exposure of the samples to the temperature condition of 90 °C resulted in ATS increases of 24.46 and 33.78% for Eagle Ford and Wolfcamp shales, respectively. Then, for samples exposed to 220 °C, ATS decreases of 6.11 and 5.32% were respectively recorded for Eagle Ford and Wolfcamp shales. The experimental results of this research will facilitate models’ development towards tensile strength predictions and failure pattern analysis and quantifications in the LFF driven hydraulic fracturing of shale gas reservoirs.
Occupational Safety Analysis for COVID-Instigated Repurposed Manufacturing Lines: Use of Nanomaterials in Injection Moulding
Authors: Damilos Spyridon , Saliakas Stratos , Kokkinopoulos Ioannis , Karayannis Panagiotis , Karamitrou Melpo , Trompeta Aikaterini-Flora , Charitidis Costas , Koumoulos Elias P.
Published: June 2022

The COVID-19 pandemic instigated massive production of critical medical supplies and personal protective equipment. Injection moulding (IM) is considered the most prominent thermoplastic part manufacturing technique, offering the use of a large variety of feedstocks and rapid production capacity. Within the context of the European Commission-funded imPURE project, the benefits of IM have been exploited in repurposed IM lines to accommodate the use of nanocomposites and introduce the unique properties of nanomaterials. However, these amendments in the manufacturing lines highlighted the need for targeted and thorough occupational risk analysis due to the potential exposure of workers to airborne nanomaterials and fumes, as well as the introduction of additional occupational hazards. In this work, a safety-oriented failure mode and effects analysis (FMEA) was implemented to evaluate the main hazards in repurposed IM lines using acrylonitrile butadiene styrene (ABS) matrix and silver nanoparticles (AgNPs) as additives. Twenty-eight failure modes were identified, with the upper quartile including the seven failure modes presenting the highest risk priority numbers (RPN), signifying a need for immediate control action. Additionally, a nanosafety control-banding tool allowed hazard classification and the identification of control actions required for mitigation of occupation risks due to the released airborne silver nanoparticles.
Neoliberal Hegemonic Masculinity and McMindfulness: The Need for Buddhist Values and Principles in Mindful Masculinity Programs
Authors: Forbes David
Published: June 2022

This paper explores how certain Buddhist-inspired principles such as impermanence of self and compassion for all (metta) and the practice of mindfulness can contribute to challenging ways in which young men adopt troublesome aspects of systemic patriarchy. It (1) briefly examines the problem of systemic patriarchy in its most dominant forms, neoliberal hegemonic masculinity and right-wing racist authoritarian masculinity; (2) critically discusses examples of mindfulness education and counseling programs for young men that have been severed from their Buddhist origins (McMindfulness) that attempt to challenge young men around patriarchal beliefs and thoughts but end up reproducing neoliberal hegemonic masculinity; (3) briefly considers the problem of McMindfulness and its relation to Buddhism and neoliberal hegemonic and mindful masculinity; and (4) offers Buddhist perspectives as part of a counter-view that may serve within programs as an alternative to current forms of patriarchy while including and renewing the aforementioned Buddhist principles.
Ruminal Bacterial Communities and Metabolome Variation in Beef Heifers Divergent in Feed Efficiency
Authors: Clemmons Brooke A. , Mulon Pierre-Yves , Anderson David E. , Ault-Seay Taylor B. , Henniger Madison T. , Schneider Liesel G. , Staton Meg , Voy Brynn H. , Donohoe Dallas R. , Campagna Shawn R. , McLean Kyle J. , Myer Phillip R.
Published: June 2022

This study determined potential microbial and metabolic biomarkers of feed efficiency in Angus heifers. Seventeen ruminal cannulated Angus heifers underwent a 70-day feed efficiency trial. Residual feed intake was used to determine high and low feed efficient heifers. On day 70 of the trial, rumen content and blood were collected and used for microbial and metabolomic analyses, respectively. Bacterial populations were examined by targeting the V4 region of the 16S rRNA gene and analyzed using QIIME and SAS. Rumen fluid and serum metabolites were analyzed using MetaboAnalyst. No microbial taxa differed after false discovery rate correction, but seven did differ (p ≤ 0.05) prior to correction, including Lachnospiraceae (Other), Desulfobulbaceae, Neisseriaceae, Shuttleworthia, Corynebacterium, p-75-a5, and L7A-E11. No differences were observed in alpha diversity metrics. Beta diversity utilizing unweighted UniFrac distances analyzed via PERMANOVA was significant (p = 0.03). Several metabolites in rumen fluid metabolites were correlated with bacteria that differed by feed efficiency phenotype. The metabolites correlated with bacteria were primarily involved in nutrient signaling and microbial crude protein availability. These data suggest variation in the availability of nutrients, primarily amino acids, as well as a relationship among microbiota, metabolome, and host feed efficiency phenotypes in heifers.
Real-Time Megapixel Electro-Optical Imaging of THz Beams with Probe Power Normalization
Authors: Blanchard François , Arikawa Takashi , Tanaka Koichiro
Published: June 2022

In this work, we present a simple method to improve the spatial uniformity of two-dimensional electro-optical imaging of terahertz (THz) beams. In this system, near-field THz images are captured by fully illuminating a sample using conventional optical microscope objectives. Unfortunately, due to the linear relationship between the optical probe power and the measured THz electric field, any spatial variation in probe intensity translates directly into a variation of the recorded THz electric field. Using a single normalized background frame information map as a calibration tool prior to recording a sequence of THz images, we show a full recovery of a two-dimensional flat field for various combinations of magnification factors. Our results suggest that the implementation of dynamic intensity profile correction is a promising avenue for real-time electro-optical imaging of THz beams.
Synthesis of Vapochromic Dyes Having Sensing Properties for Vapor Phase of Organic Solvents Used in Semiconductor Manufacturing Processes and Their Application to Textile-Based Sensors
Authors: Lee Junheon , Kim Duyoung , Kim Taekyeong
Published: June 2022

Two vapochromic dyes (DMx and DM) were synthesized to be used for textile-based sensors detecting the vapor phase of organic solvents. They were designed to show sensitive color change properties at a low concentration of vapors at room temperature. They were applied to cotton fabrics as a substrate of the textile-based sensors to examine their sensing properties for nine organic solvents frequently used in semiconductor manufacturing processes, such as trichloroethylene, dimethylacetamide, iso-propanol, methanol, n-hexane, ethylacetate, benzene, acetone, and hexamethyldisilazane. The textile sensor exhibited strong sensing properties of polar solvents rather than non-polar solvents. In particular, the detection of dimethylacetamide was the best, showing a color difference of 15.9 for DMx and 26.2 for DM under 300 ppm exposure. Even at the low concentration of 10 ppm of dimethylacetamide, the color change values reached 7.7 and 13.6, respectively, in an hour. The maximum absorption wavelength of the textile sensor was shifted from 580 nm to 550 nm for DMx and 550 nm to 540 nm for DM, respectively, due to dimethylacetamide exposure. The sensing mechanism was considered to depend on solvatochromism, the aggregational properties of the dyes and the adsorption amounts of the solvent vapors on the textile substrates to which the dyes were applied. Finally, the reusability of the textile sensor was tested for 10 cycles.
Feature Refine Network for Salient Object Detection
Authors: Yang Jiejun , Wang Liejun , Li Yongming
Published: June 2022

Different feature learning strategies have enhanced performance in recent deep neural network-based salient object detection. Multi-scale strategy and residual learning strategies are two types of multi-scale learning strategies. However, there are still some problems, such as the inability to effectively utilize multi-scale feature information and the lack of fine object boundaries. We propose a feature refined network (FRNet) to overcome the problems mentioned, which includes a novel feature learning strategy that combines the multi-scale and residual learning strategies to generate the final saliency prediction. We introduce the spatial and channel ‘squeeze and excitation’ blocks (scSE) at the side outputs of the backbone. It allows the network to concentrate more on saliency regions at various scales. Then, we propose the adaptive feature fusion module (AFFM), which efficiently fuses multi-scale feature information in order to predict superior saliency maps. Finally, to supervise network learning of more information on object boundaries, we propose a hybrid loss that contains four fundamental losses and combines properties of diverse losses. Comprehensive experiments demonstrate the effectiveness of the FRNet on five datasets, with competitive results when compared to other relevant approaches.
Learning Dynamics and Control of a Stochastic System under Limited Sensing Capabilities
Authors: Zadenoori Mohammad Amin , Vicario Enrico
Published: June 2022

The operation of a variety of natural or man-made systems subject to uncertainty is maintained within a range of safe behavior through run-time sensing of the system state and control actions selected according to some strategy. When the system is observed from an external perspective, the control strategy may not be known and it should rather be reconstructed by joint observation of the applied control actions and the corresponding evolution of the system state. This is largely hurdled by limitations in the sensing of the system state and different levels of noise. We address the problem of optimal selection of control actions for a stochastic system with unknown dynamics operating under a controller with unknown strategy, for which we can observe trajectories made of the sequence of control actions and noisy observations of the system state which are labeled by the exact value of some reward functions. To this end, we present an approach to train an Input–Output Hidden Markov Model (IO-HMM) as the generative stochastic model that describes the state dynamics of a POMDP by the application of a novel optimization objective adopted from the literate. The learning task is hurdled by two restrictions: the only available sensed data are the limited number of trajectories of applied actions, noisy observations of the system state, and system state; and, the high failure costs prevent interaction with the online environment, preventing exploratory testing. Traditionally, stochastic generative models have been used to learn the underlying system dynamics and select appropriate actions in the defined task. However, current state of the art techniques, in which the state dynamics of the POMDP is first learned and then strategies are optimized over it, frequently fail because the model that best fits the data may not be well suited for controlling. By using the aforementioned optimization objective, we try to to tackle the problems related to model mis-specification. The proposed methodology is illustrated in a scenario of failure avoidance for a multi component system. The quality of the decision making is evaluated by using the collected reward on the test data and compared against the previous literature usual approach.
CFHBA-PID Algorithm: Dual-Loop PID Balancing Robot Attitude Control Algorithm Based on Complementary Factor and Honey Badger Algorithm
Authors: Lin Jianan , Zheng Rongjia , Zhang Yirong , Feng Jinkai , Li Wei , Luo Kaiqing
Published: June 2022

The PID control algorithm for balancing robot attitude control suffers from the problem of difficult parameter tuning. Previous studies have proposed using metaheuristic algorithms to tune the PID parameters. However, traditional metaheuristic algorithms are subject to the criticism of premature convergence and the possibility of falling into local optimum solutions. Therefore, the present paper proposes a CFHBA-PID algorithm for balancing robot Dual-loop PID attitude control based on Honey Badger Algorithm (HBA) and CF-ITAE. On the one hand, HBA maintains a sufficiently large population diversity throughout the search process and employs a dynamic search strategy for balanced exploration and exploitation, effectively avoiding the problems of classical intelligent optimization algorithms and serving as a global search. On the other hand, a novel complementary factor (CF) is proposed to complement integrated time absolute error (ITAE) with the overshoot amount, resulting in a new rectification indicator CF-ITAE, which balances the overshoot amount and the response time during parameter tuning. Using balancing robot as the experimental object, HBA-PID is compared with AOA-PID, WOA-PID, and PSO-PID, and the results demonstrate that HBA-PID outperforms the other three algorithms in terms of overshoot amount, stabilization time, ITAE, and convergence speed, proving that the algorithm combining HBA with PID is better than the existing mainstream algorithms. The comparative experiments using CF prove that CFHBA-PID is able to effectively control the overshoot amount in attitude control. In conclusion, the CFHBA-PID algorithm has great control and significant results when applied to the balancing robot.
An Edge-Fog Architecture for Distributed 3D Reconstruction and Remote Monitoring of a Power Plant Site in the Context of 5G
Authors: Vidal Vinicius , Honório Leonardo , Pinto Milena , Dantas Mario , Aguiar Maria , Capretz Miriam
Published: June 2022

It is well known that power plants worldwide present access to difficult and hazardous environments, which may cause harm to on-site employees. The remote and autonomous operations in such places are currently increasing with the aid of technology improvements in communications and processing hardware. Virtual and augmented reality provide applications for crew training and remote monitoring, which also rely on 3D environment reconstruction techniques with near real-time requirements for environment inspection. Nowadays, most techniques rely on offline data processing, heavy computation algorithms, or mobile robots, which can be dangerous in confined environments. Other solutions rely on robots, edge computing, and post-processing algorithms, constraining scalability, and near real-time requirements. This work uses an edge-fog computing architecture for data and processing offload applied to a 3D reconstruction problem, where the robots are at the edge and computer nodes at the fog. The sequential processes are parallelized and layered, leading to a highly scalable approach. The architecture is analyzed against a traditional edge computing approach. Both are implemented in our scanning robots mounted in a real power plant. The 5G network application is presented along with a brief discussion on how this technology can benefit and allow the overall distributed processing. Unlike other works, we present real data for more than one proposed robot working in parallel on site, exploring hardware processing capabilities and the local Wi-Fi network characteristics. We also conclude with the required scenario for the remote monitoring to take place with a private 5G network.
Recent Advances in Rapid and Highly Sensitive Detection of Proteins and Specific DNA Sequences Using a Magnetic Modulation Biosensing System
Authors: Roth Shira , Margulis Michael , Danielli Amos
Published: June 2022

In early disease stages, biomolecules of interest exist in very low concentrations, presenting a significant challenge for analytical devices and methods. Here, we provide a comprehensive overview of an innovative optical biosensing technology, termed magnetic modulation biosensing (MMB), its biomedical applications, and its ongoing development. In MMB, magnetic beads are attached to fluorescently labeled target molecules. A controlled magnetic force aggregates the magnetic beads and transports them in and out of an excitation laser beam, generating a periodic fluorescent signal that is detected and demodulated. MMB applications include rapid and highly sensitive detection of specific nucleic acid sequences, antibodies, proteins, and protein interactions. Compared with other established analytical methodologies, MMB provides improved sensitivity, shorter processing time, and simpler protocols.
Analysis of the Vibration Characteristics of a Leaf Spring System Using Artificial Neural Networks
Authors: Çetinkaya Mehmet Bahadır , İşci Muhammed
Published: June 2022

The real-time vibrations occurring in a leaf spring system may cause undesirable effects, such as stresses, strains, deflections, and surface deformations over the system. In order to detect the most appropriate working conditions in which the leaf spring system will work more stably and also to design optimized leaf spring systems, these external effects have to be detected with high accuracy. In this work, artificial neural network-based estimators have been proposed to analyze the vibration effects on leaf spring systems. In the experimental studies carried out, the vibration effects of low, medium, and high-pressure values applied by a hydraulic piston on a steel leaf spring system have been analyzed by a 3-axial accelerometer. After the experimental studies, the Radial Basis Artificial Neural Network (RBANN) and Cascade-Forward Back-Propagation Artificial Neural Network (CFBANN) based nonlinear artificial neural network structures have been proposed to analyze the vibration data measured from the leaf spring system under relevant working conditions. The simulation results represent that the RBANN structure can estimate the real-time vibrations occurring on the leaf spring system with higher accuracy and reaches lower RMS error values when compared to the CFBANN structure. In general, it can be concluded that the RBANN and CFBANN network structures can successfully be used in the estimation of real-time vibration data.
Different Sampling Frequencies to Calculate Collective Tactical Variables during Competition: A Case of an Official Female’s Soccer Match
Authors: Errekagorri Ibai , Castellano Julen , Los Arcos Asier , Rico-González Markel , Pino-Ortega José
Published: June 2022

The objective of the study was to assess the impact of the sampling frequency on the outcomes of collective tactical variables during an official women’s soccer match. To do this, the first half (lasting 46 min) of an official league match of a semi-professional soccer team belonging to the Women’s Second Division of Spain (Reto Iberdrola) was analysed. The collective variables recorded were classified into three main groups: point-related variable (i.e., change in geometrical centre position (cGCp)), distance-related variables (i.e., width, length, height, distance from the goalkeeper to the near defender and mean distance between players), and area-related variables (i.e., surface area). Each variable was measured using eight different sampling frequencies: data every 100 (10 Hz), 200 (5 Hz), 250 (4 Hz), 400 (2.5 Hz), 500 (2 Hz), 1000 (1 Hz), 2000 (0.5 Hz), and 4000 ms (0.25 Hz). With the exception of cGCp, the outcomes of the collective tactical variables did not vary depending on the sampling frequency used (p > 0.05; Effect Size < 0.001). The results suggest that a sampling frequency of 0.5 Hz would be sufficient to measure the collective tactical variables that assess distance and area during an official soccer match.