Adeno-associated viral (AAV) vectors can be used for gene delivery. AAV.CAP-Mac was recently developed; it can cross the blood-brain barrier and transduce cells throughout the CNS. However, some brain regions were not transduced in adult rhesus monkeys. Additionally, AAV vectors can only package 5 kb of DNA. Also, AAV vectors may be genotoxic and cytotoxic, especially at high doses. Finally, AAV vectors are very expensive to produce at sufficiently high titers for treatment. Off-the-shelf cell-based delivery systems wherein the cells can infiltrate the target tissue and be hyper-motile would be ideal. Also, mRNA-based gene editing would be a transient treatment, and thus be much safer.

The relationship between the structure characteristics and performances of coal based hydrogenation isomeric base oil (CTL) and metallocene catalyzed coal based polyalphaolefin (mPAO) base oil was clarified here. CTL and mPAO were compared with typical petroleum based and natural gas based commercial API Class III and IV base oils. Pressurized differential scanning calorimetry (PDSC), Rotary Bomb Oxidation Test (RBOT) and four-balls friction tester were used to evaluate the oxidation stability and lubrication performance of base oils under different working conditions. The sensitivity of different base oils to typical antioxidants and extreme pressure antiwear agents was compared. Specially, the composition and structure of CTL base oil are obviously different from GTL and mineral base oil. The coal-based CTL and mPAO base oils exhibit commendable viscosity-temperature properties, characteristics, coupled with low-temperature fluidity, fire safety, and minimal evaporation loss. The lubricating properties, oxidation stability and the sensitivity to extreme pressure antiwear agents of CTL are close to those of similar base oils. But the sensitivity of CTL to typical antioxidants is relatively poor. Besides, compared with commercial PAO base oil, mPAO has lower isomerization degree and fewer isomerization types. The oxidation stability and sensitivity to typical antioxidants of mPAO base oil are comparable with those of commercial PAO base oil, while its lubrication performance and sensitivity to typical extreme pressure antiwear agents are significantly better than those of commercial PAO base oil.

The rapid increase in the number of mobile phone base stations (MPBS) has raised global concerns about the potential adverse health effects of exposure to radiofrequency electromagnetic fields (RF-EMF). The application of machine learning techniques can enable healthcare professionals and policymakers to proactively address concerns surrounding RF-EMF exposure near MPBS. In this study, we investigated the potential of machine learning models to predict health symptoms associated with RF-EMF exposure in individuals residing near MPBS.We utilized support vector machine (SVM) and random forest (RF) algorithms, incorporating 11 predictors related to participants' living conditions. A total of 699 adults participated in the study, and model performance was assessed using sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve (AUC). The SVM-based model demonstrated strong performance, achieving accuracies of 85.3%, 82%, 84%, 82.4%, and 65.1% for headache, sleep disturbance, dizziness, vertigo, and fatigue, respectively. The corresponding AUC values were 0.99, 0.98, 0.920, 0.89, and 0.81. Compared to the RF model and a previously developed model, the SVM-based model exhibited higher sensitivity, particularly for fatigue, with sensitivities of 70.0%, 83.4%, 85.3%, 73.0%, and 69.0% for these five health symptoms. Particularly for predicting fatigue, sensitivity and AUC were significantly improved (70% vs 8% and 11.1% for SVM, MLPNN, and RF, respectively, and 0.81 vs 0.62 and 0.64, for SVM, MLPNN, and RF, respectively). These findings suggest that machine learning methods, specifically SVM, hold promise in effectively managing health symptoms in individuals residing near or planning to settle in the vicinity of MPBS.

Recently, federated learning (FL) has been receiving great attention as an effective machine learning method to avoid the security issue in raw data collection as well as to distribute the computing load to edge devices. However, even though wireless communications is a essential part for implementing FL in edge networks, there have been a few works that analyze the effect of wireless networks on FL. In this paper, we investigate FL in small-cell networks where multiple base stations (BSs) and users are located according to homogeneous Poisson point process (PPP) with different densities. We comprehensively analyze the effects of geographic node deployment on the model aggregation in FL on the basis of stochastic geometry-based analysis. We derive the closed-form expressions of coverage probability with tractable approximations and discuss the minimum required BS density for achieving a target model aggregation rate in small-cell networks. Our analysis and simulation results provide insightful information for understanding the behaviors of FL in small-cell networks, and it can be exploited as a guideline for designing the network facilitating the wireless FL.

Background: The outbreak of the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) resulted in the global COVID-19 pandemic. The urgency for an effective SARS-CoV-2 vaccine has led to the development of a first series of vaccines at unprecedented speed. The discovery of SARS-CoV-2 spike-glycoprotein mutants, however, and consequentially the potential to escape vaccine-induced protection and increased infectivity, demonstrates the persisting importance of monitoring SARS-CoV-2 mutations to enable early detection and tracking of genomic variants of concern. Results: We developed the CoVigator tool with three components: 1) a knowledge base that collects new SARS-CoV-2 genomic data, processes it and stores its results; 2) a comprehensive variant calling pipeline; 3) an interactive dashboard highlighting the most relevant findings. The knowledge base routinely downloads and processes virus genome assemblies or raw sequenc-ing data from the COVID-19 Data Portal (C19DP) and the European Nucleotide Archive (ENA), respectively. The results of the variant calling pipeline are visualized through the dashboard in the form of tables and customizable graphs, making it a versatile tool for tracking SARS-CoV-2 variants. We put a special emphasis on the identification of intrahost mutations and make available to the community what is, to the best of our knowledge, the largest dataset on SARS-CoV-2 intrahost mutations. In the spirit of open data, all CoVigator results are available for download. The CoVigator dashboard is accessible via covigator.tron-mainz.de. Conclusion: With increasing demand worldwide in genome surveillance for tracking the spread of SARS-CoV-2, CoVigator will be a valuable resource of up-to-date list of mutations, which can be incorporated into global efforts to sustainably prevent or treat infections.

The functions of annexin A1 (ANXA1) that is expressed on membranes and in cytoplasmic granules have been fully described. Nonetheless, the role of this protein in protecting against DNA damage in the nucleus is still emerging and requires further investigation. Here, we investigated the involvement of ANXA1 in DNA damage response in placental cells. Placenta was collected from ANXA1 knockout mice (AnxA1-/-) and pregnant women with gestational diabetes mellitus (GDM). The placental morphology and ANXA1 expression, which are related to the modulation of cellular response markers in the presence of DNA damage, were analyzed. Total area of AnxA1-/- placenta was smaller because of reduced labyrinth zone, enhanced DNA damage, and impaired base excision repair (BER) enzymes, which resulted in the induction of apoptosis in the labyrinthine and junctional layers. The placentas from pregnant women with GDM showed reduced expression of AnxA1 in the villous compartment, increased DNA damage, apoptosis, and reduction of enzymes involved in the BER pathway. Our translational data provide valuable insights into the possible involvement of ANXA1 in the response of placental cells to oxidative DNA damage and represent advancement in investigations on the mechanisms involved in placental biology.

For the emerging autonomous swarm technology, from the perspective of systems science and systems engineering, there must be some novel elements and methods to aggregate multiple systems into a group, which distinguish with the general components with specific functions, and we expect to provide the presentation of their existence in the swarm development processes. The inspiration of our methodology origins from the integration of swarm ontology, multi-paradigm modeling, multi-agent system, cyber-physical system, etc. Therefore, we choose the model-driven technology as a framework to acquire an approach of model representation across the multiple levels of abstraction and composition. The autonomous strategic mechanism is defined and formed in parallel with ConOps analysis and systems design, so as to effectively solve the cognitive problem of emergence caused by the nonlinear causation among individual and whole behaviors. This approach highlights to use the MBSE processes and their artifacts to embed the meso mechanism to integrate the operational and the functional, and which means to connect the macro and micro aspects in formalism and so to become a whole with its expected goals, and then to verify and validate within a L-V-C simulation environment.

In winter sports, the equipment often comes into contact with snow or ice, and this contact generates a force that resists motion. In some sports, such as cross-country skiing, this resistive force can significantly affect the outcome of a race, as a small reduction in this force can give an athlete an advantage. Researchers have examined the contact between skis and snow in detail, and to fully understand this friction, the entire ski must be studied at various scales. At the macro scale, the entire geometry of the ski is considered and the apparent contact between the ski and the snow is considered and at the micro scale the contact between the snow and the ski base ski-base textures. In the present work, a method for characterising contact between the ski-base texture and virtual snow will be presented. Six different ski-base textures will be considered. Five of them are stone-ground ski bases, and three of them have linear longitudinal textures with a varying number of lines and peak-to-valley height, and the other two are factory-ground “universal” ski bases. The sixth ski base has been fabricated by a steel-scraping procedure. In general, the results show that a ski base texture with a higher Spk-value has less real contact area, and that the mutual differences can be large for surfaces with similar Sa-values. The average interfacial separation is, in general, correlated with the Sa-value, where a “rougher” surface exhibits a larger average interfacial separation. The results for the reciprocal average interfacial separation, which is related to the Couette type of viscous friction, were in line with the general consensus that a “rougher” texture performs better at high speed than a “smoother” one, and it was found that a texture with high Sa and Spk values resulted in a low reciprocal average interfacial separation and consequently low viscous friction. The reciprocal average interfacial separation was found to increase with increasing real contact area, indicating a correlation between the real area of contact and the Couette part of viscous friction.

Abiotic stresses, including drought, salinity, cold, heat, and heavy metals, extensively reduce global agricultural production. Approaches such as conventional breeding and transgenic breeding have been widely used to cope with these environmental stresses. The clustered regularly interspaced short palindromic repeat- Cas (CRISPR/Cas) based gene-editing tool has revolutionized due to its simplicity, accessibility, adaptability, flexibility, and wide applicability. This system has a great potential to build up crop varieties with enhanced tolerance against abiotic stresses. In this review, we summarize the most recent findings on understanding the mechanism of abiotic stress response in plants and the application of CRISPR/Cas mediated gene-editing system towards enhanced tolerance to drought, salinity, cold, heat, and heavy metals stresses. Furthermore, in this review, we highlighted the recent advancements in prime editing and base editing tools for crop improvement.

Using density functional theory (DFT) and the information-theoretic approach (ITA) quantities to appreciate the energetics and properties of biopolymers is still an unaccomplished and ongoing task. To this end, we studied the building blocks of nucleic acid base pairs and small peptides. For base pairs, we have dissected the relative importance of energetic components by using two energy partition schemes in DFT. Our results convincingly show that the exchange-correlation effect predominantly governs the molecular stability of base pairs while the electrostatic potential plays a minor but indispensable role, and the steric effect is trivial. Furthermore, we have revealed that simple density-based ITA functions are in good relationships with molecular polarizabilities for a series of 30 hydrogen-bonded base pairs and all 20 natural α-amino acids, 400 dipeptides, and 8000 tripeptides. Based on these lines, one can easily predict the molecular polarizabilities of larger peptides, even proteins as long as the total molecular wavefunction is available, rather than solving the computationally demanding coupled-perturbed Hartree-Fock (CPHF) equation or its DFT counterpart coupled-perturbed Kohn-Sham (CPKS) equation.

In the diagnosis of olfactory neuroblastoma (ONB), the presence of S-100–positive sustentacular cells surrounding the tumor is important; however, these are also present in normal nasal sinus epithelium. Although ONB often has a different final diagnosis, complete resection of the tumor has a good prognosis and minimally affects the patient's treatment plan. When the tumor extends around the internal carotid artery (ICA), complete resection is difficult due to the high risk of vascular injury; revascularization using a high-flow bypass can avoid this complication. In the present case, the tumor was located in the left sphenoid sinus and extended around the ICA. Preoperative biopsy tissue was positive for neuroendocrine markers and slightly positive for S-100 protein, leading to a diagnosis of ectopic ONB. High-flow bypass revascularization with trapping of the ICA allowed complete tumor resection. The postoperative histopathological diagnosis was neuroendocrine carcinoma, showing no S-100 protein–positive cells. There was no sign of recurrence two and a half years after surgery without additional treatment. This case demonstrates that the presence of S-100 protein–positive cells in ONB may be misleading. Although misdiagnosis of ectopic ONB should be anticipated, a complete resection of the tumor is an effective treatment strategy.

Laser shock peening as an innovative surface treatment technology can effectively improve the fatigue life, sur-face hardness, corrosion resistance, and residual compressive stress. Compared with the laser shock peening, the warm laser shock peening (WLSP) is a new surface treatment technology to improve materials’ surface performances, which takes advantage of thermal mechanical effects on stress strengthening and micro-structure strengthening, results in more stable distribution of the residual compressive stress under heating and cyclic loading process. In this paper, the microstructure of GH4169 nickel super-alloy processed by WLSP technology with differ-ent laser parameters were investigated. The proliferation and tangling of dislocations in GH4169 were observed and the dislocation density increased after WLSP treatment. The influences of different treatment by LSP and WLSP on the microhardness distribution of the surface and along cross-sectional depth were investi-gated. The microstructure evolution of the GH4169 alloy being shocked with WLSP were studied by TEM. The effect of temperature on the stability of high temperature microstructure and properties of GH4169 alloy WLP was investigated.

Through the half-unit circle area computation using the integration of the corresponding curve power series representation, we deduce a slow converging positive infinite series to $\pi$. However, by studying the remainder of that series we establish sufficiently close inequalities with equivalent lower and upper bound terms allowing us to estimate, more precisely, how the series approaches $\pi$. We use the obtained inequalities to compute up to four-digit denominator, what are in this sense, the best rational numbers that can replace $\pi$. It turns out that the well-known convergents of the continued fraction of $\pi$, $22/7$ and $355/113$ called, respectively, Yuel\"{u} and Mil\"{u} in China are the only ones found. Thus we apply a similar process to find rational estimations to $\pi+e$ where $e$ is taken as the power series of the exponential function evaluated at $1$. For rational numbers with denominators less than $2000$, the convergent $920/157$ of the continued fraction of $\pi+e$ turns out to be the only rational number of this type.

Vertical-channel organic dual-gate/base transistors would be highly interesting since vertical organic transistors are the fastest organic transistors demonstrated today. However, incorporating a dual gate/base structure into an ultra-short channel vertical architecture represents a substantial challenge. Here, we successfully realize a new device concept of vertical organic permeable dual-base transistors (OPDBTs), where either of both base electrodes can be used to change the on-currents and tune the threshold voltages. The optimized devices yield a high on-current density of 1.54 A cm^-2 and a large current gain of 9.2×10⁵, corresponding to a high transmission value of 99.998%. The detailed operation mechanisms are investigated by calibrated TCAD simulations with the Poole-Frenkel mobility model, Gaussian density of states and tunneling model. Finally, high-performance logic circuits, e.g. inverter, NAND/AND computation functions are demonstrated with one single OPDBT operating at supply voltages of < 2.0 V. We believe that OPDBTs offer a compact and technologically simple hardware platform with excellent application potential for vertical-channel organic transistors in complex logic circuits.

Background: Iranian traditional medicine is a holistic school of medicine with a long prolific history. It describes numerous concepts and the relationships between them. However, no unified terminology has been proposed for the concepts of this medicine up to the present time. Considering the extensive use of concepts in the numerous textbooks written by the scholars over centuries, comprehending the totality of the terminology is obviously a very challenging task. To resolve this issue and overcome the obstacles, and code the concepts in a reusable manner, constructing an ontology of the concepts of Iranian traditional medicine seems a necessity.Methods: Makhzan al-Advieh, an encyclopedia of materia medica compiled by Mohammad Hossein Aghili Khorasani, was selected as the resource to create an ontology of Mizaj. The steps followed to accomplish this task included (1) compiling the list of classes for Mizaj; (2) arranging the classes in taxonomy; (3) determining object properties and their cardinalities; (4) specifying annotation properties including codes, labels, synonyms, and definitions for each concept; (5) reviewing the fields pertaining to Mizaj of all monographs in Makhzan al-Advieh. The ontology was created using Protégé with adherence to the principles of ontology development provided by the Open Biological and Biomedical Ontology (OBO) foundry. Results: Mizaj ontology was constructed with a final inclusion of 105 classes, three object properties, and 1078 axioms in the Iranian Traditional Medicine General Ontology database, IrGO, freely available at http://jafarilab.com/irgo/. An indented tree view and an interactive graph view using WebVOWL were used to visualize the ontology. All classes were linked to their instances in the UNaProd database to create a knowledge-base of Mizaj. Conclusion: We constructed an ontology-based knowledge base of ITM concepts of Mizaj in the domain of materia medica to help offer a shared and common understanding of this concept, enable reuse of the knowledge, and make the assumptions explicit. Extending IrGO will bridge the gap between traditional and conventional schools of medicine and help guide future research on new treatment options.

Here we evaluate the chemistry of mineral soil solutions collected by suction lysimeters in a small mountain catchment that was affected by acidification-related spruce die-back. The aim was to obtain new insights into spatial patterns of nutrient partitioning during acidification recovery. This was achieved by comparing nutrient concentrations in soil solutions, collected along a V-shaped valley, with those in runoff. Five nests of suction lysimeters were installed in the 33-ha UDL catchment at different topographic positions (hilltops, slopes and valley). Following a 1-year equilibration, monthly samples of soil solutions were collected over a 2-year period. In the vicinity of each lysimeter nest, soil pits were excavated for a study of soil chemistry. Soil solutions were analyzed for SO42-, NO3-, DOC, NH4+, Na+, K+, Ca2+, Mg2+, and total dissolved Al concentrations, DOC and pH. For a P release estimation, ammonium oxalate extraction of soil samples was performed. Comparison of soil water data from this study with other European studies indicated that major environmentally relevant chemical species at UDL had concentrations similar to median concentrations across numerous previously acidified sites. CEC (≤ 58 meq kg-1) and BS (≤ 13 %), however, were significantly lower at UDL than at other European sites, documenting incomplete recovery from acidification. Spatial trends and seasonality in soil water chemistry support belowground inputs from mineral-stabilized legacy pollutants and soil nutrients. Seasonal variability of soil water sulfate and nitrate was significant. High nitrate in soil solutions during summer originated during the preceding dormant season, and high sulfate concentrations observed during the winter originating from recycled organic S during the summer. Higher concentrations of SO42-, NO3-, and base cations in runoff than in soil solutions may be explained by lateral surficial runoff leaching pollutants and nutrients from very shallow soil horizons. Nearly 30 years after peak acidification, solutions in mineral subsoil at UDL exhibited similar concentrations of SO42-, Ca2+ and Mg2+ as median values at the Pan-European International Co-operative Program (ICP) Forest sites, yet NO3- concentrations were an order of magnitude higher than the ICP sites. Calcium applied on soil surface by liming 32 to 11 years ago affected runoff more than soil solutions, suggesting contribution of both shallow soil water and groundwater to runoff.

Collisional mountain belts commonly develop intramontane basins from mechanical and isostatic subsidence during orogenic development. These frequently display a relict top surface, evidencing a change interval from basin infilling to erosion often via capture or overspill. Such surfaces provide markers that inform on orogenic growth patterns via climate and base level interplay. Here, we describe the top surface from the Sorbas Basin, a key intramontane basin within the Betic Cordillera (SE Spain). The surface is fragmentary comprising high elevation hilltops and discontinuous ridges developed onto the variably deformed final basin infill outcrop (Gochar Formation). We reconstruct surface configuration using DEM interpolation and apply ¹⁰Be/²⁶Al cosmonuclides to assess surface formation timing. The surface is a degraded Early Pleistocene erosional pediment developed via autogenic switching of alluvial fan streams under stable dryland climate and base level conditions. Base level lowering since the Middle Pleistocene focused headwards incision up interfan drainages, culminating in fan head capture and fan morphological preservation within the abandoned surface. Post abandonment erosion has lowered the basin surface by 31 m (average) and removed ~5.95 km³ of fill. Regional basin comparisons reveal a phase of Early Pleistocene surface formation, marking landscape stability following the most recent Pliocene-Early Pleistocene mountain building. Post-surface erosion rate quantification is low and in accordance with ¹⁰Be denudation rates typical of the low uplift Betic Cordillera.

Bone growth plate abnormalities and skull shape defects are seen in hypophosphatasia, a heritable disorder in humans that occurs due to deficiency of Tissue Nonspecific Alkaline Phosphatase (TNAP, Alpl) enzyme activity. Abnormal development of the cranial base growth plates (synchondroses) and abnormal skull shapes have also been demonstrated in global TNAP-/- mice. To distinguish local vs. systemic effects of TNAP on skull development, we utilized P0-Cre to knockout TNAP only in cranial neural crest derived tissues using TNAP flox mice. Here we show that TNAP deficiency in cranial neural crest leads to leads to skull shape defects and deficient growth of the intersphenoid synchondrosis (ISS). ISS chondrocyte abnormalities included increased proliferation in resting and proliferative zones with decreased apoptosis in hypertrophic zones. ColX expression is increased, indicative of premature differentiation in the absence of TNAP. Sox9 expression is increased in both resting and prehypertrophic zones of mutant mice. Expression of PTHrP and IHH were also increased. Finally, cranial base organ culture revealed that inorganic phosphate (Pi) and pyrophosphate (PPi) have specific effects on cell signaling and phenotype changes in the ISS. Together, these results demonstrate that TNAP expression in growth plate chondrocytes is essential for normal development, and that the mechanism likely involves Sox9, PTHrP, IHH and PPi.

The production of photovoltaic modules is increasing to reduce greenhouse gas emissions. However, this results in a significant amount of waste at the end of their lifespan. Therefore, recycling these solar panels is important for environmental and economic reasons. However, collecting and separating Crystalline silicon, Cadmium Telluride, and Copper indium gallium selenide panels can be challenging, especially in underdeveloped countries. The innovation of this work is to develop a process to recycle all solar panel waste. The dissolution of all metals is studied through the leaching process as the main step of the flowchart. In the first step of leaching, silver can be recovered 98% by 0.5 nitric acid. Then, the second and third step involves the use of glycine for base metals dissolution, followed by the leaching of valuable metals with hydrochloric acid. The effect of parameters such as initial pH, acid concentration, solid/liquid ratio, and Hydrogen peroxide concentration are studied. The results show that Cu, Pb, Sn, Zn, Cd, In, Ga, and Se can be recovered until about 100% under optimal conditions. The optimal conditions for the dissolution of Cu, Zn, and Cd were the glycine concentration of 0.5 M, Temperature of 25 ˚C, the solid/liquid ratio of 10 gr/l, and 1% of Hydrogen peroxide. The optimized glycine concentration for the leaching of lead and tin was 1.5M. Indium and gallium were recovered to 100% by the use of 5M Hydrochloric acid, S/L=10gr/l, and T=45 ˚C. Separation of selenium and tellurium occurred by 0.5 M HCl at a temperature of 60 ˚C. Additionally, for the first time, a general outlook for the recycling of various end-of-life solar panels is suggested.

In general, isolators and dampers used in seismically isolated buildings are designed to be isotropic in any horizontal direction. However, in the case of buildings with plan irregularities, their nonlinear responses depend on the direction of seismic loading. To discuss the influence of the angle of seismic incidence (ASI) on the nonlinear response of irregular building structures, it is important to define the angle of the critical axis of the horizontal ground motion. One possible choice is the “principal axis of ground motion” proposed by Arias (1970). However, because this principal axis is independent of the natural period of a structure, it could be complicated to use for seismically isolated structures with long natural periods. In this study, the influence of the ASI of long-period pulse-like seismic input on an irregular base-isolated building is investigated. First, the angle of the principal axis of ground motion is defined in terms of the cumulative energy input. Then, a nonlinear time-history analysis of a five-story irregular base-isolated building is performed using 10 long-period pulse-like ground motion records considering various ASIs. The results show that, compared with the principal axis of ground motion proposed by Arias, defining the principal axis of ground motion in terms of the cumulative energy input is more suitable for discussions concerning the influence of the ASI on the response of an irregular base-isolated building.

Sickle cell disease is characterized by stiff, “sickled” red blood cells that have difficulty moving through the bloodstream and do not efficiently carry oxygen. It is an inherited disease with severely limited treatment options, and is caused by a point mutation. Its prevalence in black and brown communities makes the already limited treatment options even less accessible. Base editing and prime editing are two relatively recent discoveries in the field of genome editing and were developed after the groundbreaking discovery of the CRISPR Cas9 system. While not fully tested, they hold a lot of promise in providing alternative treatment options for sickle cell disease. Both editing systems are able to install individual point mutations in the beta globin gene, which is where the sickle cell mutation occurs, and can thus cure sickle cell disease (in theory). In this paper we outline the mechanisms of CRISPR-Cas9 systems and base and prime editing, and provide insight into how to apply them to treat SCD. Further investigation should be done on specific editing systems and designs to use to ensure optimal treatment of SCD.

The C5-methylation of uracil to form 5-methyluracil (m⁵U) is a ubiquitous base modification of nucleic acids. Four enzyme families have converged to catalyze this methylation using different chemical solutions. Here, we investigate the evolution of 5-methyluracil synthase families in Mollicutes, a class of bacteria that has undergone extensive genome erosion. Many mollicutes have lost some of the m⁵U methyltransferases present in their common ancestor. Cases of duplication and subsequent shift of function are also described. For example, most members of the Spiroplasma subgroup, use the ancestral tetrahydrofolate-dependent TrmFO enzyme, to catalyze the formation of m⁵U54 in tRNA, while a TrmFO paralog (termed RlmFO) is responsible for m⁵U1939 formation in 23S RNA. RlmFO has replaced the S-adenosyl-l-methionine (SAM)-enzyme RlmD that adds the same modification in the ancestor and which is still present in mollicutes from the Hominis subgroup. Another paralog of this family, the TrmFO-like protein, has a yet unidentified function that differs from the TrmFO and RlmFO homologs. Despite having evolved towards minimal genomes, the mollicutes possess a repertoire of m⁵U modifying enzymes that is highly dynamic and has undergone horizontal transfer. This emphasizes the necessity for combining bioinformatics predictions with empirical testing and structural information to get a reliable functional annotation of these enzymes.

Over the years, sustainability, impact on the environment, as well as the operation expenditure have been a major concern to the deployment of mobile cellular base stations worldwide. This is because the mobile cellular base stations are known to consume a high percentage of power within the mobile cellular network. Such energy consumption contributes to the emission of Greenhouse Gases (GHG) through the use of conventional diesel generating a set. As a result, the mobile cellular operators are faced with the dilemma of minimising the power consumption, GHG emission, and the operation cost, while improving the Quality of Service of the networks. In attempting to find a solution, this study presents the feasibility and simulation of a solar photovoltaic (PV) with battery hybrid power system (HPS) as a predominant source of power for a specific mobile cellular base station site situated in Soshanguve area of the city of Pretoria, South Africa. It also presents the technical development, showed the environmental advantage and cost benefits of using a solar PV-battery HPS to power a base station site of a 24 hrs daily load of 241.10 kWh/d and the peak load of 20.31 kW as compared to using the HPS of solar PV-diesel generating set-battery. The solar resource pattern for the city of Pretoria was collected from The National Aeronautics and Space Administration and modelled statistically. Thus, the statistical modelling done using solar radiation resource exposure characteristic patterns of Pretoria, South Africa, revealed an average annual daily solar radiation of 5.4645 Wh/m2/d and 0.605 clearness index. The simulation and the design were done using the Hybrid Optimization Model for Electric Renewables and Matlab/Simulink software. The simulation finding shows that the HPS of solar PV-battery combination has about 59.62 % saving on Net Present Cost, Levelized Cost of Energy, and 80.87% saving on Operating cost as against conventional BS powered with Gen Set-Battery.

Some optimal control problems need metaheuristics in searching for the optimal solution, especially when the process has certain characteristics like the Photobioreactor for Algae Growth (distributed parameter, nonlinearities, etc.). Particle Swarm Optimization (PSO) algorithms within control structures are a realistic approach; their task is often to predict the optimal control values working with a process model (PM). Owing to numerous numerical integrations, there is a big computational effort that is reflected in a large controller execution time. The authors propose to replace the PSO predictor with a machine learning model that has “learned” the quasi-optimal behavior of the couple (PSO, PM); the training data is obtained through closed-loop simulations over the control horizon. The new controller should preserve the process’s quasi-optimal control. In identical conditions, the process evolutions must also be quasi-optimal. The multiple Linear Regression and the Regression Neural Networks were considered as predicting models. The paper first proposes algorithms for collecting and aggregating data sets for the learning process. Algorithms for constructing the machine learning models, implementing the controllers, and closed-loop simulations are also proposed. The simulations prove that the two machine learning predictors have learned the PSO predictor’s behavior such that the process evolves almost identically. The resulting controllers’ execution time drastically decreased while keeping their optimality.

Acoustic focusing of particle flow in microfluidics has been shown to be an efficient tool for particle separation for various chemical and biomedical applications. The mechanism behind the method is the selective effect of the acoustic radiation force on distinct particles. In this way, they can be selectively focused and separated. The technique can also be applied under stationary conditions, i.e., in the absence of fluid flows. In this study, the manipulation of self-propelled particles, such as Janus particles, in an acoustofluidic setup is investigated. In experiments with self-propelled Janus particles and passive beads, we explore the interplay between self-propulsion and the acoustic radiation force. Our results demonstrate unusual and potentially useful effects such as selective trapping, escape and assisted escape in binary mixtures of active and passive particles. We also analyze various aspects related to the behavior of Janus particles in acoustic traps in the presence and absence of flows.

Laser powder bed fusion can fabricate porous structure through lattices, but it remains a challenge to prepare micropores (

Container crane has been widely used for port operation. However, the structure of port container crane is large, which always lead to crane damage under the vibration and strong wind. Therefore, a method for vibration reduction of container crane structure based on particle damping technology is proposed. In this investigation, the scale 1:80 crane model is built, the equivalent mechanical model is also established to preliminary verify the effect of vibration suppression. Furthermore, the dependence of vibration suppression effect on the key parameters of the damper, i.e., filling material, filling rate, particle size, and installation position of dampers are analyzed through experiments. The results indicate that the vibration peak of the crane structure displayed in Simulink oscilloscope is weakened and lags behind, the installation of the damper brings the effect of vibration suppression for the crane, the vibration suppression effect reaches 25%; the crane mode obtains the best vibration suppression effect under the condition that the material filled in the damper has a large density and elastic modulus, sufficient collision space and high collision frequency, and the dampers are installed far away from the crane center of gravity. The optimum parameters of the damper obtained from experiments, 12 mm lead beads, filling rate of 60%, installed in the distal ends within the strength range of the forearm of the crane. It is thus concluded that the particle damping technology has provided an effective way in wind and vibration reduction for container crane.

The base excitation of mechanical equipment can result in pipeline system vibration which seriously affects the safe operation of the equipment. Particle damping technology is based on the particle collision dissipation principle to realize the structural vibration energy dissipation. This paper introduces the particle damping method into the vibration control of pipeline system. A particle damper has been designed for the structural characteristics of the pipeline. The influence of the material and structure of the pipeline particle damper, the external excitation and other parameters on the energy dissipation characteristics of particle damping are revealed. The energy dissipation mechanism of the pipeline particle collision damper under various parameter is analyzed. A pipeline vibration reduction test system with particle damping has been established. The effects of different excitation conditions, damper materials and number of unit structures of particle damper on the vibration damping effect of pipeline systems are investigated comparatively. The influence of damper parameters on the vibration suppression of pipeline system is obtained. The research in this paper can provide technical references for vibration suppression of pipeline systems.

The interest on amorphous carbon thin films with low secondary electron yield (SEY) has been increasing in the last years, to mitigate electron multipacting in particle accelerators and in RF devices. Previous works found that the SEY increases with the hydrogen amount and correlates with the Tauc gap. In this work, we analyse films produced by magnetron sputtering with different contents of hydrogen and deuterium, incorporated via target poisoning and sputtering of CxDy molecules. XPS was implemented to estimate the phase composition of the films. The maximal SEY was found to decrease linearly with the fraction of the graphitic phase in the films. These results are supported by Raman scattering and UPS. The graphitic phase decreases almost linearly for hydrogen and deuterium concentrations between 12% and 46% (at.), but abruptly decreases when the concentration reaches 53%. This vanishing of the graphitic phase is accompanied by a strong increase of SEY and of the Tauc gap. These results suggest that the SEY is not dictated directly by the concentration of H/D but by the fraction of graphitic phase. The results are supported by a model used to calculate SEY of films consisting of a mixture of graphitic and polymeric phases.

The process of shock wave focusing can make the strength of shock waves be continuously accumulated and turned into detonation wave in Pulse Detonation Engine (PDE). However, its effective application needs the inlet jets be in high temperature and velocity, which is difficult to be satisfied under certain conditions. Therefore, in this paper, metal magnesium assisted detonation initiation is proposed and the effect of magnesium particle addition on the shock wave focusing process in a kerosene-fueled PDE with cavity configuration is investigated through numerical simulation. The result showed that when the temperature of the premixed fuel/air jets injected in opposite direction was set as 650 K, the collision of leading shock waves on the central axis was the main source of energy deposition and the shock wave focusing could make the detonation be initiated in the cavity. When the temperature of jets is reduced to 550 K, fuel ignition and detonation could not be achieved through shock wave focusing. Then adding metal magnesium particles into the combustor made the energy deposition be enhanced and the detonation be induced. The diffusion of metal particles can significantly change the structure, motion, merging and dissipation of vortices in the flow field. Generally, the shock wave focusing process is basically not affected with metal particles injection. Therefore, this method can be successfully employed for detonation initiation in the cavity when the fuel/air premixed jet temperature is not high for PDE.

These years have witnessed growing research on applying rheology in grinding and flotation treatment of finely disseminated ores. The slurry rheology has long been identified as the comprehensive effect of inter-particle interactions, including their aggregation (coagulation and flocculation) and dispersion states in slurry, which are more impactive under the fine-particle effect. In this regard, rheology has the potential to play a significant role in interpreting the flowing and deforming phenomenon of inter-particle aggregates, particle-bubble aggregates, and flotation froth. Though much attention has been paid to the rheological effect in industrial suspension, this has not been the case for mineral grinding and flotation for fine particles. The influential mechanism of rheology on the sub-processes of mineral processing has not been systemically concluded and revealed thoroughly, without which the underpinning mechanism for enhancing the processing efficiency has been difficult to discover. This paper reviews the current application and importance of rheology in the fine mineral processing, and the potential research direction in the field is proposed.

We introduce two symmetric concepts to physics: “distance” (space and time in one) and “wavematter” (electromagnetic wave packet and matter in one). We claim that physics has chosen the wrong concept of time: It is not aware that the time of a moving object flows in a direction other than my time. We provide 15 proofs for our claim by solving 15 mysteries of physics graphically! For example, we prove that length contraction and time dilation are actually geometrical effects in a 4D manifold that we call “Euclidean spacetime” (ES). We prove that the discrepancy in calculating the Hubble constant stems from a systematic error in the redshift measurement. We prove that what I deem wave, deems itself matter, which solves wave–particle duality. We even untangle quantum entanglement without the issue of non-locality. We finally understand why alternative theories of Euclidean relativity have failed: They are all based on four dimensions of space rather than distance. A huge amount of energy was injected into ES at a point that we take as origin. Ever since has this energy been moving radially away at the speed of light. We live in the 3D hypersurface of an expanding 4D hypersphere. Hyperspherical coordinates have the great advantage that they reduce all that is ever happening to just one formula. So, it is the Theory of Everything in these coordinates: “Energy is covering radial distance which, divided by Euclidean time, is equal to the speed of light.” Acceleration and force like gravitation emerge from a rotation of objects in ES and a subsequent projection to 3D space. Matching the symmetry simplifies physics.

Dirac’s equation depicts electron mass as either positive or negative. Taken as correct description of nature, the equation identifies electron mass as ‘electrically active’ and therefore fundamentally different from the ordinary, ‘electrically passive’ mass. Following this cue, I demonstrate that electron mass (m_e) is the natural elementary mass: positive (m_e⁺) and negative (m_e^–) elementary masses neutralise to an elementary unit of the electrically passive mass (2m_e⁰). Further, I show that electron mass (m_e^± ) and the electrostatic field (e_f^±) surrounding it compose an elementary charge (e^±), thereby relating charge to mass. Two plain principles underlie these findings. 1) Electric charge and gravitational mass have a common root: positive (e⁺) and negative (e^–) charges coexist as neutral charge (2e⁰), which is the quantum of gravitational mass. 2) Charge is a static (nonrelativistic) ‘atom of electricity’ and obeys the laws of electrostatics; electron is the same ‘atom of electricity’ at ultrahigh (relativistic) speed and obeys the laws of electrodynamics. That is, charges are electricity at rest; electrons are electricity in motion – ‘same physical entities two behavioural identities.’ A decisive proof that this paradigm shift correctly portrays is that it verifiably unifies Newton’s law of gravity and Coulomb’s law of electrostatics to: 8G/m_pm_e = K/e²; where G and K are the respective constants, m_p the proton mass, m_e the electron mass, and e the elementary charge. Ultimately, the insights simplify matter to pure ‘atoms’ of positive and negative electricity.

Global optimization is an imperative development of local optimization because there are many problems in artificial intelligence and machine learning requires highly acute solutions over entire domain. There are many methods to resolve the global optimization, which can be classified into three groups such as analytic methods (purely mathematical methods), probabilistic methods, and heuristic methods. Especially, heuristic methods like particle swarm optimization and ant bee colony attract researchers because their effective and practical techniques which are easy to be implemented by computer programming languages. However, these heuristic methods are lacking in theoretical mathematical fundamental. Fortunately, minima distribution establishes a strict mathematical relationship between optimized target function and its global minima. In this research, I try to study minima distribution and apply it into explaining convergence and convergence speed of optimization algorithms. Especially, weak conditions of convergence and monotonicity within minima distribution are drawn so as to be appropriate to practical optimization methods.

Currently, various industrial processes are carried out in fluidized bed reactors, such as fermentation, water treatment, and algae growth. Knowing its internal dynamics is fundamental for the intensification of these processes. This work assesses the motion of fluidized calcium alginate spheres under the influence of an upward fluid flow within a 1.2 m high and 0.1 m inner diameter acrylic column. The Radioactive Particle Tracking technique is a proper methodology to study the internal dynamics of these kinds of equipment. Liquid-Solid Fluidized Bed is compared with the Gas-Liquid-Solid Fluidized Bed operation mode in terms of mixing behavior. Data gathered is analyzed in view of Shannon entropy as a dynamic mixing measure. Mixing times are found to be of the same order of magnitude. However, the Liquid-Solid Fluidized Bed achieves a lower homogenization degree. Also, we found good agreement between two criteria for assessing stability for the mixed state: the Shannon Entropy time-series plateau and the Glansdorff-Prigogine criterion based on Fisher information.

An analysis is presented of the possible existence of a second anomalous dipole moment of Dirac’s particle next to the one associated with the angular momentum. It includes a discussion why, in spite of his own derivation, Dirac has doubted about its relevancy. It is shown why since then it has been overlooked and why it has vanished from leading textbooks. A critical survey is given on the reasons of its reject, including the failure of attempts to measure and the perceived violations of time reversal symmetry and charge-parity symmetry. It is emphasized that the anomalous electric dipole moment of the pointlike electron (AEDM) is fundamentally different from the quantum field type electric dipole moment of an electron (eEDM) as defined in the standard model of particle physics. The analysis has resulted into the identification of a third type Dirac particle, next to the electron type and the Majorana particle. It is shown that, unlike as in the case of the electron type, its second anomalous dipole moment is real valued and is therefore subject to polarization in a vector field. Examples are given that it may have a possible impact in the nuclear domain and in the gravitational domain.

As currently understood, the Dirac theory employs a 4 x1 type wavefunction. This 4x1 Dirac wavefunction is acted upon by a 4x4 Dirac Hamiltonian operator, in which process, four independent particle solutions result. Insofar as the real physical meaning and distinction of these four solutions, it is not clear what these solutions really mean. We demonstrate herein that these four independent particle solutions can be brought together under a single roof wherein the Dirac wavefunction takes a new form as a 4x4 wavefunction. In this new formation of the Dirac wavefunction, these four particle solutions precipitate into three distinct and mutuality dependent particles that are eternally bound in the same region of space. Given that Quarks are readily found in a mysterious threesome cohabitation-state eternally bound inside the Proton and Neutron, we make the suggestion that these Dirac particles might be Quarks. For the avoidance of speculation, we do not herein explore this idea further but merely present it as a very interesting idea worthy of further investigation. We however must say that, in the meantime, we are looking further into this very interesting idea, with the hope of making inroads in the immediate future.

The Eastern Mediterranean is a highly populated area with air quality problems as well where climate change already is noticed by higher temperatures and changing precipitation pattern. The anthropogenic aerosol affects health and changing concentra-tions and properties of the atmospheric aerosol affect radiation balance and clouds. Continuous long-term observations are essential in assessing the influence of anthro-pogenic aerosols on climate and health. We present 6 years of observations from Navarino Environmental Observatory (NEO), a new station located at the south west tip of Pelo-ponnese, Greece. The two sites at NEO, were evaluated to show the influence of the local meteorology but also to assess the general background aerosol possible. It was found that the background aerosol was originated from aged European aerosols and was strongly influenced by biomass burning, fossil fuel combustion, and industry. When subsiding into the boundary layer, local sources contributed in the air masses moving south. Mesoscale meteorology determined the diurnal variation of aerosol properties such as mass and number by means of typical sea breeze circulation, giving rise to pronounced morning and evening peaks in pollutant levels. While synoptic scale meteorology, mainly large-scale air mass transport and precipitation, strongly influenced the season-ality of the aerosol properties.

Particle swarm optimization (PSO) is an effective algorithm to solve the optimization problem in case that derivative of target function is inexistent or difficult to be determined. Because PSO has many parameters and variants, I propose a general framework of PSO called GPSO which aggregates important parameters and generalizes important variants so that researchers can customize PSO easily. Moreover, two main properties of PSO are exploration and exploitation. The exploration property aims to avoid premature converging so as to reach global optimal solution whereas the exploitation property aims to motivate PSO to converge as fast as possible. These two aspects are equally important. Therefore, GPSO also aims to balance the exploration and the exploitation. It is expected that GPSO supports users to tune parameters for not only solving premature problem but also fast convergence.

Several particles are not observed directly, but only through their decay products. We consider the possibility that they might be fakeons, i.e. fake particles, which mediate interactions but are not asymptotic states. A crucial role to determine the true nature of a particle is played by the imaginary parts of the one-loop radiative corrections, which are affected in nontrivial ways by the presence of fakeons in the loop. The knowledge we have today is sufficient to prove that most non directly observed particles are true physical particles. However, in the case of the Higgs boson the possibility that it might be a fakeon remains open. The issue can be resolved by means of precision measurements in existing and future accelerators.

Plant pathogens utilize effectors to subvert host cell biology for facilitating infection. However certain effectors, called as the avirulence proteins, trigger immune responses in the host. AvrPi54 is an avirulence protein from fungus Magnaporthe oryzae which induces the defense reactions in rice cells that contain Pi54 resistance gene. The characterization of such proteins and elucidation of their function facilitate the understanding of the mechanism of disease establishment. In present study, physiochemical properties of AvrPi54 were analysed using computational methods. We found that mature AvrPi54 is a small, hydrophobic and secretary protein with 134 amino acids. It is rich in small amino acids with no significant homology with other proteins in databases. The gene ORF was cloned in pET28a(+) vector and expressed in E. coli BL21(DE3)pLysS. The protein was purified using affinity chromatography. Transient expression of the gene in epidermal cells of onion bulb is a powerful tool to predict the subcellular localization in plant cells. We fused AvrPi54 to eYFP and transformed epidermal cell layer of onion bulb. Fused protein localized to the plasma membrane and nucleus of plant cells. Therefore, AvrPi54 might be functioning in the host cell as transcription factor or chromatin remodelling factor to modify pathogenesis-related processes.

In this article various heuristic approaches are discussed to solve the dark matter phenomenon by the concept of vacuum polarization. They are compared with a more fundamental approach, based upon an entropy model of the visible universe. They all make use of some kind of gravitational dipole. These dipoles seem to violate Einstein’s equivalence principle between inertial mass and gravitational mass. It is shown how the paradox can be solved by a quantum mechanical principle.

Inertial microfluidics offers high throughput, label-free, easy to design, and cost-effective solutions and is a promising technique based on hydrodynamic forces (passive techniques) instead of external ones, which can be employed in lab-on-a-chip and micro-total-analysis-systems for focusing, manipulation, and separation of microparticles in chemical and biomedical applications. The current work, studies the focusing behavior of microparticles in an asymmetric curvilinear microchannel. For this purpose, focusing behavior, including position and band width, of microparticles of diameters of 10, 15 and 20 µm, which served as representatives of different cells, in an asymmetric curvilinear microchannel with curvature angle of 280° was experimentally studied at flow rates from 400 to 2700 µL/min (corresponding to Reynolds numbers between 30 and 205). The results revealed that the largest distance between focusing bands of 20 µm and 10 µm microparticles as well as between focusing bands of 15 µm and 10 µm was obtained at Reynolds number of 121. For the case of microparticles of diameters 20 µm and 15 µm, the largest distance was seen at Reynolds number of 144. The focusing band width became smaller in the asymmetric microchannel so that focusing could be more clearly observed in this configuration.

Silver nanoparticles (AgNPs) have been demonstrated to restrain bacterial growth while maintaining the minimal risk in development of bacterial resistance and human cell toxicity that conventional silver compounds exhibit. Several physical and chemical methods have been reported to synthesize AgNPs. However, these methods are expensive and involve heavy chemical reduction agents. An alternative approach to produce AgNPs in a cost-effective and environmentally friendly way employs a biological pathway using various plant extracts to reduce metal ions. The size control issue and the stability of nanoparticles remain some of the latest challenges in such methods. In this study, we used two different concentrations of fresh leaf extract of the plant Arbutus Unedo (LEA) as a reducing and stabilizing agent to produce two size variations of AgNPs. UV-Vis spectroscopy, Dynamic Light Scattering, Transmission Electron Microscopy and zeta potential were applied for the characterization of AgNPs. Both AgNP variations were evaluated for their antibacterial efficacy against the gram-negative species Escherichia coli and Pseudomonas aeruginosa, as well as the gram-positive species Bacillus subtilis and Staphylococcus epidermidis. Although significant differences have been achieved in the nanoparticles’ size by varying the plant extract concentration during synthesis, the antibacterial effect was almost similar.

We have successfully developed curcumin nanosuspension aimed for oral delivery. The main purpose is to improve bioavailability through enhancing its solubility. The nanoparticles were stabilized using various stabilizers including polyvinyl pyrrolidone (PVP), polyvinyl alcohol (PVA), sodium carboxymethylcellulose (Na-CMC), d-alpha tocopheryl polyethylene glycol 1000 succinate (TPGS), and sodium dodecyl sulfate (SDS). The average diameter of particles, microscopic appearance, and sedimentation of each preparation was observed and compared. Each stabilizer demonstrated different degree of inhibition of particle aggregation under electrolyte-containing simulated gastrointestinal (GIT) fluid. Non-ionic stabilizers (PVA, PVP, and TPGS) has shown to preserve the nanosuspension stability against electrolytes. In contrast, strong ionic surfactants such as SDS were found to be very sensitive to electrolytes. The results can provide useful information for the formulators to choose the most suitable stabilizers by considering the nature of stabilizers and physiological characteristics of target site of the drug.

At the highest level of endurance sports, the differences in finishing times are small, so equipment is constantly being constantly improved to enhance the athletes' performance. For instance, one dominant resistive force in connection with cross-country skiing is the friction between the skis and snow and since the 1930s, research designed to understand and reduce this friction has been ongoing. The mechanisms involved in ski-snow friction include compaction, micro-ploughing, adhesion, viscosity, and water-bridging. Of these, adhesive and viscous friction have been most studied, while much less is presently known about compaction, micro-ploughing, and water-bridging. At the macro-scale, the ski-camber profile plays a key role in determining whether, with respect to friction, a particular cross-country ski is suitable for use under a given set of conditions. Through its influence on where ski-snow contact occurs, this ski-camber profile has a profound impact on adhesive and viscous friction, micro-ploughing, the formation of water bridges, and the rate of compaction. Different contact zones with different apparent areas of contact and pressure have been found to be most suitable for different conditions. In addition, the micro-scale texture of the ski base is also an important determinant of ski-snow friction. Topographical measurements of this texture can be achieved with white-light interferometer and recent characterisation has focused on the mechanical properties of contact. In numerous tribological studies the interactions between features at different scales are modelled. In most tribological systems, features on several scales influence friction and ski-snow contact is certainly no exception. Accordingly, the current investigation was designed to evaluate the multi-scale properties of different combinations of two skis with two different base textures. The real area of contact and the average interfacial separation and total average reciprocal interfacial separation between the ski and snow were taken into consideration. We found that different macro- and micro-scale properties of the ski favour different mechanisms of friction. Both the profile of the ski camber and texture of the base play decisive roles in determining viscous friction. At the same time, the texture of the ski base exerts a greater impact on the average real contact pressure, real contact area and minimal average interfacial separation between the ski and snow than does the ski-camber profile.

Background: Shared value creation in Base of the Pyramid (BoP) communities is a crucial process towards building sustainable societies. BoP communities in developing countries represent more than four billion people who live on low incomes with limited access to basic products and services. Current or emerging technologies offer promising solutions for organisations pursuing manufacturing opportunities in BoP communities. This study seeks to explore the literature on how BoP communities may become active participants in sustainably manufacturing products using micro-manufacturing factories. The research question posed is: What are the core concepts that need to be taken into consideration for creating shared value through micro-manufacturing factories in BoP communities? Method: A Systematised Literature review (SLR) was completed following the Preferred Reporting Items for Systematic reviews and Meta-Analysis (PRISMA) method for data selection criteria and analysis. The SLR is used to explore the state of literature with regards to creating manufacturing shared value in BoP communities with the objective to identify study gaps and to explore shared value creation concepts. Results: Literature indicates BoP initiatives that have pursued to engage BoP communities through various innovation strategies. The findings of the review is organised under three strategic pillars: Capability building strategy, Implementation process, and Growth strategy. The capability building strategy defines the users’ intention to create shared value in BoP communities with Micro-manufacturing factories (MMF). It is followed by the implementation process which guides the users to create manufacturing shared value in BoP communities. This is followed by a growth strategy to scale for impact.

Conventional plant breeding methods exploit already existing genomic variation in plants to develop a variety in 8 to 10 years, which can decrease the genetic variability of the plant’s genome. The ever-increasing food demand for cereals crops cannot be met by traditional breeding methods. In order to increase food production in less time, there is a dire need to improve breeding methods. Several conventional and molecular breeding methods are being used to improve the crops traits. Molecular researchers have developed new genome editing tools like CRISPR/Cas9, CRISPR/Cpf1, prime editing, base editing, dcas9 epigenetic modification, and several other transgene-free genomes editing approaches. These genome editing tools can improve the desired traits precisely and efficiently. Moreover, a newly developed breeding method “Speed Breeding” has revolutionized the agriculture by shortening the crop cycle. It can produce 5-6 generations of cereals in a year. In this review, we have summarized all these conventional and molecular breeding approaches to improve cereal crops.

Construction and demolition waste (CDW) represents 1/3 of the weight of all-waste produced. Increasing their recycling and reutilization with recycled aggregates (RA) means closing the life cycle of construction materials. Research has been carried out on artificial aggregates from the exclusive crushing of structural concrete waste in selective demolitions (CDWRConc). This study analyses the use of recycled concrete as graded aggregate (GARConc) and in cement soil (CSRConc). The material complies with the requirements as a road base, although due to the low values of resistance to fragmentation these materials are adequate for use in sensitive road systems and other places such as urban roads and car parks. The sensitive road systems are infrastructures in places of great natural wealth and low traffic intensity, with an annual average of heavy vehicle traffic (AADTh) below 50 vhp/d. As soluble salt contents have been detected, additional waterproofing or drainage measures must be adopted to prevent water infiltration into the layers made up of CDWRHorm. Finally, the high initial values of UCS allow the temporary passage of light vehicles over CSRConc after 3 days.

Background: Ongoing molecular profiling studies enabled by advances in biomedical technologies are producing vast amounts of ‘omic’ data for early detection, monitoring, and prognosis of diverse diseases. A major common limitation is the scarcity of biological samples, necessitating integrative modeling frameworks that can make optimal use of available data for disease classification tasks. Related data sets are often available from different studies, but may have been generated using different technology platforms. Thus, there is a critical need for flexible modeling methods that can handle data from diverse sources to facilitate the discovery of robust biomarkers that underlie disease regulatory processes. Results: In this paper, we introduce a novel framework called Knowledge Augmented Rule Learning (KARL), which incorporates two sources of knowledge, domain, and data, for pattern discovery from small and high-dimensional datasets, such as transcriptomic data. We propose KARL as a transfer rule learning framework in which knowledge of the domain is transferred to the learning process on data in order to 1) improve the reliability of the discovered patterns, and 2) study the knowledge of the domain when used along with data for modeling. In this work, we generated KARL models on gene expression datasets for five types of cancer, including brain, breast, colon, lung, and prostate. As our knowledge of the domain, we used the Ingenuity Knowledge Base (IKB) to extract genes related to hallmarks of cancer and annotated these prior relationships before learning classifiers from these datasets. Conclusions: Our results show that KARL produces, on average, rule models that are more robust classifiers than the baseline without such background knowledge, for our tasks of cancer prediction using 25 publicly available gene expression datasets. Moreover, KARL helped us learn insights about previously known relationships in these gene expression datasets, along with new relationships not input as known, to enable informed biomarker discovery for cancer prediction tasks. KARL can be applied to modeling similar data from any other domain and classification task. Future work would involve extensions to KARL to handle hierarchical knowledge to derive more general hypotheses to drive biomedicine.

Reasonable allocation of production plans and saving the overall electricity cost are crucial for large manufacturing conglomerates, which is an effective way for conglomerates to realize open-source and cost-saving. This paper develops an optimization model of off-site industrial production scheduling for enterprises in response to the problems of high electricity costs due to the irrational allocation of production schedules on the demand side of China's electric power and the difficulty of promoting industrial and commercial distributed photovoltaic (PV) projects in China. The model makes full use of the conditions of different PV resources and different electricity prices in different places to optimize the scheduling of industrial production in different places. The model is embedded with two sub-models of the electricity price prediction model and distributed photovoltaic kWh cost model to complete the model parameters, in which the electricity price prediction model utilizes the LSTM neural network. The integrated model is then solved by the particle swarm algorithm. To verify the effectiveness of the model in solving the problem of off-site production scheduling on the demand side of electricity, the research team researched two off-site pharmaceutical factories belonging to the same large pharmaceutical company. Finally, the research data were substituted into the model for solving, and it was concluded that the optimization model could significantly reduce the cost of electricity consumption of the enterprise by about 7.9 %.

Effects of oxygen content on microstructure and creep property of FGH96 superalloy were investigated. When oxygen content increased from 135ppm to 341ppm, prior particle boundary (PPB) rose from degree 2 to degree 3, and the size of γ′ phase on PPB enlarged from 1.07μm to 1.27μm, and MC carbide size grew from 77.4nm to 104.0nm. Meanwhile, the steady creep rate accelerated form 4.34×10-3 h-1 to 1.87×10-2 h-1, and the creep rupture life shortened from 176h to 94h, and the creep rupture mode transferred from intergranular and transgranular mixed fracture to along PPB fracture. During creep, the micro-twins formation and gliding will be restrained by ∑3 boundaries. FGH96 superalloy with higher oxygen content contains less ∑3 boundaries and its micro-twins cross slipped instead of single direction slip in lower oxygen content superalloy. Consequently, specimen with higher oxygen content creeped faster and raptured earlier.

This work is aimed at investigating the capabilities and limits of the mid-fidelity numerical solver DUST for the evaluation of wind turbines aerodynamic performance. In particular, this study was conducted by analysing the benchmarks NREL- 5MW and Phase VI wind turbines, widely investigated in literature by from experimental and numerical activities. The work started by simulating simpler configuration of the NREL- 5MW turbine to progressively integrate complexities such as shaft tilt, cone effects and yawed inflow conditions, offering a detailed portrayal of their collective impact on turbine performance. A particular focus was then given to the evaluation of aerodynamic responses from the tower and nacelle, as well as aerodynamic behavior in yawed inflow condition, crucial for optimizing farm layouts. In the second phase, the work was focused on NREL Phase VI turbine due to the availability of experimental data on this benchmark case. Comparison of DUST simulations results with both experimental data and high-fidelity CFD tools shows the robustness and adaptability of this mid-fidelity solver for this applications, thus opening a new scenario for the use of such mid-fidelity tools for the preliminary design of novel wind turbines configurations or complex environments as wind farms, characterised by robust interactional aerodynamics.

River bed materials serve multiple environmental functions as a habitat for aquatic invertebrates and fishes. At the same time, the particle size of the bed material reflects the tractive force of the flow regime in a flood and provides useful information for flood control. The traditional river bed particle size surveys, such as sieving, require time and labor to investigate river bed materials. The authors proposed a method to classify aerial images taken by unmanned aerial vehicle (UAV) using convolutional neural networks (CNN), our previous study showed that terrestrial riverbed material could be classified with high accuracy. In this study, we attempted to classify riverbed materials distributed in shallow waters where the bottom can be seen from UAVs. After training the CNN to classify the images with the same grain size as being in the same class even if the surface flow types taken overlapping the riverbed material were different, the total accuracy reached 90.3%. Moreover, the proposed method was applied to the wide-ranging area to determine the distribution of the particle size. In parallel, the microtopography was surveyed using Lidar-UAV, and the relationship between the microtopography and particle size distribution was discussed. In the steep section, coarse particles were distributed and formed a rapid. Fine particles were deposited on the upstream side of those rapids, where the slope had become gentler due to the damming. There was good agreement between the microtopographical trends and the grain size distribution.

The interactions of metal ions with fulvic acids resulted in changes in the particle size and charge. Particle size distribution was trimodal for fulvic acids, bimodal for fulvic complexes with calcium and magnesium, and copper-fulvic complexes had only one size fraction. The compensation of negative charge of carboxylic and phenolic functional groups by positive charged metal ions resulted in the increase in zeta potential which was getting closer to zero in the case of copper-fulvic complexes. However, all metal humic complexes behaved as colloidally unstable which resulted in visually observable sedimentation. Calorimetric measurements provided positive values of changes in enthalpy which indicated endothermic processes. In contrast quantum chemical calculations as well as experiments with model compounds provided negative values indicated exothermic processes. Changes in Gibbs energy were determined as negative and changes in entropy as positive which meant spontaneous processes.

An axial wind turbine's performance is analyzed numerically using geometrical and operational parameters. The performance of an axial wind turbine is simulated using three-dimensional computational fluid dynamics (CFD) and compared with experimental data, which confirms the validity of the assumptions and method used. A study of the effects of air in clean and sand particlesy conditions is then conducted. A study was also conducted on mechanical power and the impact of the blade tip on the extension of the vortex. It has been found that different sand particle sizes have a significant impact on wind performance numerically from 0.1 to 0.9, and the results indicate that mechanical power and thrust increase as wind velocity increases, but larger sand particle sizes reduce power, thrust, and torque as wind velocity increases. The turbulence intensity causes the pressure distribution on the walls to be irregular, thereby increasing mechanical power and propulsion force. Moreover, as the wind velocity increases, the tip speed ratio increases and the vortexes are subsequently extended.

Objective To measure, exposure to PM2.5 particles in outdoor smoking areas and changes in breathing rates in patients with asthma or chronic obstructive pulmonary disease (COPD). Setting Sixty venues in Czechia, Ireland and Spain, in an open, non-randomised, clinical trial. Participants We studied 60 patients-30 asthma patients (Female 63.3%), with a mean age (+/-standard deviation [SD]) of 47.4 (19.0 SD), and 30 COPD patients (Female 51.6%), mean age 63.5 (10.1 SD), smokers, non-smokers or ex-smokers, recruited through medical clinics. Intervention Patients wore a PM2.5 particle monitor (AirSpeck), and a breath monitor (RESpeck) for 24 hours to determine changes in breathing rates (Br) at rest and during a visit to an outside smoking area. Spirometry and breath CO were measured before and the day after visiting an outdoor smoking area. Results PM2.5 levels in the 60 venues were highly variable, in 1 premises levels of PM2.5 were sustained for at least 15 minutes at ≥ 2,000 µg/m3, in 4 premises, ≥ 500 (range 1,933-539) µg/m3, in 8 premises, ≥ 200(range 480-203) µg/m3, in 9 premises, ≥ 100 (range 170-108) µg/m3, in 8 premises, ≥ 40 (range 80.5- 40.1) µg/m3, in 9 premises, ≥ 25 µg/m3, in 10 premises, ≥ 10 µg/m3, in 8 premises, and ≤10 µg/m3 in only 3 premises, with a single wall. The overall breathing rates/minute (Br)did not change significantly but in 28 patients mean Br increased from 21.47 (1.74 SD) to 22.8 (2.29 SD), change of -1.35 (-1.80-0.91 C.I), p value 0.00 and mean in 29 patients Br decreased from 21.95(2.43 SD) to 20.38(2.79 SD), 1.57(1.03-2.12 C.I), p value 0.00. Conclusion Exposure to high levels of PM2.5, and associated alteration of patients’ breathing rates occurred in outdoor smoking areas despite national comprehensive smokefree laws. These exposure levels support the abolition of such areas. (Words 295) ClinicalTrials.gov ID: NCT03074734 Ethics: Approval Number: Ref: 15-103

The double nature, wave and corpuscular, of the material particles is usually considered incomprehensible as it cannot be represented visually. It is proposed to the student, in the introductory courses, as a fact justified by quantum interference experiments of which, however, no further analysis is possible. In this note we propose a description of the wave function in terms of a simple electrical analogy, which reproduces at least some of its essential properties. The aim we propose is to provide a cognitive representation of an analogical type: starting from a classical context (electrical circuits) and introducing in an appropriate way the notions of "wave" and "particle", we show how typically quantum properties such as delocalization and entanglement emerge in a natural, understandable and intuitive way.

The steady-state multiplicity of the porous, non-isothermal, catalyst pellet when two parallel and consecutive chemical reactions take place was analysed in this work. The geometry selected for the catalyst pellet is finite hollow cylinder. A numerical multigrid continuation technique with the preconditioned conjugate gradient squared as coarse grid solver was used. The continuation parameter is the dimensionless adiabatic heat rise (Prater number) for the first chemical reaction. The effect of the other governing parameters was analysed and the results are compared to those provided by the single chemical reaction.

In this study, a simple and direct numerical scheme is proposed for the similarity solution of Smoluchowski coagulation equation based on Taylor series expansion method of moment. The results show that the present method is convergence with high accuracy by comparison with previous work in the literatures.

It is shown that the relationship between gravity and quantum physics can be described in terms of the symmetry break of space due to elementary constituents, dubbed as “darks”, which constitute a universal energetic background field that extends from the cosmological level down to the nuclear level. It requires (a) the awareness of the polarisable second elementary dipole moment of a recently discovered third Dirac particle type, next to the electron-type and the Majorana-type, and (b) the awareness that Einstein’s Lambda is not a constant of nature, but, instead, a covariant integration constant with a value that depends on the scope of the cosmological system under consideration, such as solar systems and galaxies, eventually showing up as the Cosmological Constant at the level of the universe. The relationship has been made explicit by relating two major gravitational constants quantaties (the gravitational constant and Milgrom’s acceleration constant) with a single nuclear quantity (the rest mass of the pion derived from the Higgs boson value).

Nature-inspired algorithms are very popular tools for solving optimization problems inspired by nature. However, there is no guarantee that optimal solution can be obtained using a randomly selected algorithm. As such, the problem can be addressed using trial and error via the use of different optimization algorithms. Therefore, the proposed study in this paper analyzes the time-complexity and efficacy of some nature-inspired algorithms which includes Artificial Bee Colony, Bat Algorithm and Particle Swarm Optimization. For each algorithm used, experiments were conducted several times with iterations and comparative analysis was made. The result obtained shows that Artificial Bee Colony outperformed other algorithms in terms of the quality of the solution, Particle Swarm Optimization is time efficient while Artificial Bee Colony yield a worst case scenario in terms of time complexity.

Nature-inspired algorithms are very popular tools for solving optimization problems inspired by nature. However, there is no guarantee that optimal solution can be obtained using a randomly selected algorithm. As such, the problem can be addressed using trial and error via the use of different optimization algorithms. Therefore, the proposed study in this paper analyzes the time-complexity and efficacy of some nature-inspired algorithms which includes Artificial Bee Colony, Bat Algorithm and Particle Swarm Optimization. For each algorithm used, experiments were conducted several times with iterations and comparative analysis was made. The result obtained shows that Artificial Bee Colony outperformed other algorithms in terms of the quality of the solution, Particle Swarm Optimization is time efficient while Artificial Bee Colony yield a worst case scenario in terms of time complexity.

In this study, a monoethanolamine aerosol growth model was developed to investigate the aerosol growth factor. Interactions among the internal conditions in an absorber were considered in this aerosol model. Additionally, an experiment was conducted to measure aerosol particle size, for collecting in-house validation data. Sucrose was used as the aerosol nuclei instead of sulfuric acid to prevent the corrosion of equipment used in the experiment. Experimental results showed that the outlet aerosol sizes increased to the same size regardless of the sucrose concentrations. The aerosol growth model was validated using the in-house experimental data. The aerosol growth model efficiently predicted the aerosol size. For investigating aerosol growth effects, particle number concentration was determined to be the primary factor affecting aerosol growth and amine emissions. When the particle number concentration increased, the aerosol size decreased, whereas the MEA emission increased.

Classical mechanics describes the laws of motion in the macroscopic material world, while quantum mechanics describes the laws of motion in the microscopic material world that classical mechanics cannot explain, and achieves a highly accurate mathematical representation of the laws of microscopic physical motion. But even with such a successful theory, there is confusion about the probability wave. Therefore, this paper attempts to improve the physical definition of the conceptual basis of quantum mechanics, thus solving the confusion of quantum mechanical probability waves, and finally surprisingly discovered another feasible interpretation of the principle of cosmic redshift and the invariance of the speed of light.

We use a random gap model to describe a metal-insulator transition in three-dimensional semiconductors due to doping and find a conventional phase transition, where the effective scattering rate is the order parameter. Spontaneous symmetry breaking results in metallic behavior, whereas the insulating regime is characterized by the absence of spontaneous symmetry breaking. The transition is continuous for the average conductivity with critical exponent equal to 1. Away from the critical point the exponent is roughly 0.6, which may explain experimental observations of a crossover of the exponent from 1 to 0.5 by going away from the critical point.

In the past 100 years, quantum theory has achieved remarkable achievements and formed a relatively mature system, but at the same time there are still some incomplete places. For example: What is the origin of quantum? What is the origin of quantum entanglement? What is the origin of quantum mechanical wave-particle duality? This is still a problem that the existing quantum theory has not solved. Therefore, this paper attempts to seek a classic interpretation of quantum mechanics to make up for the shortcomings of existing quantum theory. In the latest research, this paper finds a classic interpretation of blackbody radiation, which can explain the discontinuity of light energy from the perspective of classical mechanics. Based on this discovery, this paper successfully explains the origin of quantum, quantum entanglement and wave-particle duality, and eliminates the confusion of quantum mechanical probability waves.

Muography is an expanding technique for the investigation of the internal structure of targets of interest in geophysics. The flux of high penetrating muons produced by primary cosmic rays is attenuated by traversing kilometer size objects like X-ray flux is attenuated through the human body. This gives the possibility to study the internal structure of volcanoes or underground cavities, e.g., starting from the measure of the muon flux transmission through the target. Many groups of researchers working with this technique have to face with high background level that afflicts the reconstruction of muon tracks near the horizontal direction. An important source of background is the scattering of particles near the detector that produces a wrong reconstruction of the incoming direction. An innovative technique based on Cherenkov radiation was investigated by means of Monte Carlo simulations developed in Geant4 toolkit and MATLAB. The results reported in this paper show that the presented technique is able to correctly distinguish the incoming direction of particles with an efficiency higher than 98%. This new kind of detector could represent an alternative for high resolution charged particle tracking also for other applications.

In this investigation magnetic γ-Al2O3 ceramic nanocomposite particles bearing epoxide functionality are prepared following a multistep process. The ultimate nanocomposite particles are named as γ-Al2O3/Fe3O4/SiO2/poly(glycidyl methacrylate (PGMA). The surface property is evaluated by carrying out the adsorption study of Remazol navy (RN), a model reactive azo dye, on both γ-Al2O3/Fe3O4/SiO2 and γ-Al2O3/Fe3O4/SiO2/PGMA nanocomposite particles. The adsorption is carried out at the point of zero charge (PZC) to neutralize the effect of particle surface charge. The adsorption rate is very fast, reached equilibrium (qe) value within five min. Due to mesoporous structure of silica layer γ-Al2O3/Fe3O4/SiO2 nanocomposite particles possessed relatively higher specific surface area and magnitude of adsorption is dependent on the total specific surface area. The introduction of epoxide functionality favored high adsorption capacity in mass per unit surface area. The adsorption process strictly followed Langmuir model. Thermodynamic equilibrium parameters implied that irrespective of surface functionality the adsorption process is spontaneous and exothermic. Pseudo-second-order rate kinetic model is more appropriate to explain the adsorption kinetics.

In this paper, an icosahedral non – body centered model to simulate the periodic structure of homogeneous particulate composites, by predicting the particle arrangement, is presented. This model has yielded three different variations which correspond at three different deterministic particle configurations. In addition, the concept of boundary interphase between matrix and inclusions was taken into account. Thus, the influence of particle vicinity was examined in parallel with the interphase concept on the thermomechanical properties of the overall material. Next, by the use of this model the authors derived a closed – form expression to estimate the thermal conductivity of this type of composites. To test the validity of the model, the theoretical values arising from the proposed formula were compared with other theoretical predictions obtained from several accurate formulae found in the literature and an adequate accordance was observed.

Gigantic particle accelerators, incredibly complex detectors, an antimatter factory and the discovery of the Higgs boson – this is part of what makes CERN famous. Only a few know that CERN also hosts the world largest Open Access initiative: SCOAP3. The Sponsoring Consortium for Open Access Publishing in Particle Physics (SCOAP3) started operation in 2014 and has since supported the publication of 19,000 Open Access articles in the field of particle physics, at no direct cost, nor burden, for individual authors worldwide. SCOAP3 is made possible by a 3,000-institute strong partnership, where libraries re-direct funds previously used for subscriptions to ’flip’ articles to ’gold Open Access’. With its recent expansion, the initiative now covers about 90% of the journal literature of the field. This article describes the economic principles of SCOAP3, the collaborative approach of the partnership, and finally summarizes financial results after four years of successful operation.

In this study, we attempted to verify the hypothesis that total metals bound to dust of different particle sizes may reflect pollution levels, but cannot predict its bioavailability and risks in human health assessments. Dust samples were collected using active sampling method; during the dry season months of November, 2014 to March, 2015 at different locations in Akure (7˚10ʹN and 5˚15ʹE). The samples were sorted into different particle sizes (< 10µm, 10 – 50 µm, >50µm), analyzed for some physicochemical properties and assessed for metals bioavailability using two-step physiological extraction method. The amount of metals (Cd, Cu, Cr, Ni, Pb, Zn and Mn) released in each particle sizes were determined using Perkin-Elmer 6000 Inductively Coupled Plasma - Atomic Emission Spectrometry (ICP-AES) analysis. The results showed that bioavailability of some metals (Cd, Ni, Pb, and Zn) decreases with increasing particle sizes, however, the reverse trend was observed for Mn, Cu and Fe concentrations. This may be attributed to some combination of physicochemical characteristics of the dust and metal speciation. Hence, it was concluded that metal bioaccessibility in dust can best be described by the knowledge of physicochemical characteristics. The exposure dose of the metals showed that cancer risks due to inhalation were very high when compared to other exposure routes (ingestion and dermal contact). The calculated non-cancer (HQ) and cancer risk (HI) for humans in the area showed values higher than unity, indicating possibility of the metals’ body burden.

Smoothed particle hydrodynamics (SPH) is regarded as a pure Lagrangian approach, which can solve fluid dynamics problems without the creation of mesh. In this paper, a paralleled SPH solver is developed to solve particle-based computational acoustics (PCA). The aim of this paper is to study the feasibility of using SPH to solve acoustic problems and to improve the efficiency of solving processes by paralleling some procedures on GPU during calculating. A stand SPH code running serially in a CPU is proposed to solve wave equation. This is a wave propagating in a two-dimensional domain. After finishing the computation, the results are compared with the theoretical solutions and they agree well. So its feasibility is verified. There are two main methods for searching neighbor particles: all-pair search method and linked-list search method. Both methods are used in different codes to simulate an identical problem and their runtimes are compared to investigate their searching efficiencies. The runtime results show that linked-list search method has a higher efficiency, which can save a lot of searching time when simulating problems with huge amounts of particles. Furthermore, the percentages of different procedures’ runtimes in a simulation are also discussed to find the most consuming one. Then, some codes are modified to run in different GPUs and their runtimes are compared with those of serial ones on a CPU. Runtime results show that the paralleled algorithm can be more than 80 times faster than the serial one. The result shows that GPU paralleled SPH computing can achieve desirable accuracy and speed in solving acoustic problems.

In this paper we report a new development on the numerical model for aluminum-steam combustion. This model is based on diffusion flame of continuum regime and the thermal equilibrium between the particle and the flow field, which can be used to calculate the aluminum particle combustion model for two phase calculation conditions. The model prediction is in good agreement with the experimental data. A new type of vortex combustor was proposed for the combustion of aluminum and steam, and the mathematical model of the two phase reacting flow with in this combustor was established. The turbulence effects are modeled using the Reynolds Stress Model (RSM) with Linear Pressure-Strain approach, and the Eddy-Dissipation model is used to simulate the gas phase combustion. Aluminum particles are injected into the vortex combustor and form a swirling flow around the chamber and their trajectories are traced using the Discrete Phase Model (DPM). The simulation results show that the vortex combustor can achieve high efficient combustion of aluminum and steam. The influencing factors, such as the eccentric distance of the inlet of aluminum particles, particle size and steam inlet diameter, etc., are studied. The work described in this paper represents an attempt to the design of a vortex combustor in order to increase aluminum combustion efficiency.

Maize is an important staple food crop in sub-Saharan Africa (SSA). However, the average grain yield on farmers’ fields falls considerably short of the demand of the region’s population. In addition, the normal endosperm maize widely consumed in SSA is deficient in vitamin A. Drought, a consequence of climate change, is a major constraint to maize production, resulting in seasonal low grain yield in farmers’ fields. The objectives of this study were to assess the performance of newly developed extra-early maturing provitamin A hybrids under managed drought and well-watered conditions, compare the outcomes of multiple trait base-index and multi-trait genotype-ideotype distance index selection procedures, and identify drought-tolerant hybrids with stable performance across contrasting environments for commercialization in SSA. One hundred and ninety provitamin A hybrids and six checks were evaluated under managed drought and well-watered conditions at Ikenne for two seasons between 2021 and 2023. A 14*14-lattice design was used for the field evaluations under both research conditions. Drought stress was achieved by the complete withdrawal of irrigation water 25 days after planting. Results revealed significant differences among the hybrids under drought and well-watered conditions. Grain yield, ears per plant, and plant aspect under managed drought were correlated to the same traits under well-watered conditions suggesting that the expression of these traits is governed by common genetic factors. Twenty-nine hybrids were identified as top-performing drought-tolerant hybrids by the multiple trait base index and multiple-trait genotype–ideotype distance index. Of the selected outstanding 29 hybrids, 34% were derived from crosses involving the tester TZEEIOR 197, demonstrating the outstanding genetic potential of this inbred line. Further analysis of the 29 selected hybrids revealed TZEEIOR 509 × TZEEIOR 197 as the hybrid that combined the most drought-tolerant adaptive traits. However, the hybrids TZEEIOR 526 × TZEEIOR 97, TZEEIOR 384 × TZEEIOR 30, TZEEIOR 515 × TZEEIOR 249, TZEEIOR 510 × TZEEIOR 197, TZEEIOR 479 × TZEEIOR 197, and TZEEIOR 458 × TZEEIOR 197 were identified as the most stable hybrids across drought and well-watered conditions. These hybrids should be extensively tested in multi-location trials for deployment and commercialization in SSA.

The present study investigates the role of a simple inerter in supplemental devices for possible implementation in the matured seismic base isolation technique. Firstly, the response of the base-isolated structure with an optimally tuned mass damper-inerter (TMDI) is investigated to see the tuning effects. The time required to tune the TMDI was found to be significantly longer than the duration of a strong-motion earthquake. There was still a reduction in the response of the isolated structure, which is primarily due to the added damping and stiffness (ADAS) of TMDI and not because of the tuning effects. Hence, it is proposed that the corresponding ADAS of the TMDI be directly added to the isolation device. Secondly, the response of the base-isolated structures with the fluid inerter damper (FID) is studied. It was observed that the inerter of the FID does not influence the displacement variance of an isolated structure under broadband earthquake excitation. It implies that the response of the isolated structure with FID is primarily controlled by its counterpart fluid damper (FD). The performance of optimal TMDI, ADAS, FID, and FD to mitigate the seismic response of the flexible multi-story base-isolated structure under real earthquake excitations is also investigated. In terms of suppressing the displacement and acceleration responses of the isolated structure, it has been found that TMDI and ADAS perform similarly. Comparing the response of the isolated structure with FID and FD demonstrated that the inerter in the FID has detrimental effects on the isolated structures, in which the top floor's acceleration and base shear are substantially increased.

Deep neural networks (DNN) have successfully delivered a cutting-edge performance in several fields. With the broader deployment of DNN models on critical applications, the security of DNNs becomes an active and yet nascent area. Attacks against DNNs can have catastrophic results, according to recent studies. Poisoning attacks, including backdoor and Trojan attacks, are one of the growing threats against DNNs. Having a wide-angle view of these evolving threats is essential to better understand the security issues. In this regard, creating a semantic model and a knowledge graph for poisoning attacks can reveal the relationships between attacks across intricate data to enhance the security knowledge landscape. In this paper, we propose a DNN Poisoning Attacks Ontology (DNNPAO) that would enhance knowledge sharing and enable further advancements in the field. To do so, we have performed a systematic review of the relevant literature to identify the current state. We collected 28,469 papers from IEEE, ScienceDirect, Web of Science, and Scopus databases, and from these papers, 712 research papers were screened in a rigorous process, and 55 poisoning attacks in DNNs were identified and classified. We extracted a taxonomy of the poisoning attacks as a scheme to develop DNNPAO. Subsequently, we used DNNPAO as a framework to create a knowledge base. Our findings open new lines of research within the field of AI security.

During the last decades, zebrafish (Danio rerio) has become one of the most important model organisms to study different physiological and biological phenomena. Research field of carbonic anhydrases (CAs) and carbonic anhydrase related proteins (CARPs) is not an exception in this. The best-known known function of CAs is the regulation of acid-base balance. However, studies performed with zebrafish, among others, have revealed important roles for these proteins in many other physiological processes, some of which have been unpredicted in the light of the previous studies and suggestions. Examples are roles in zebrafish pigmentation as well as motor coordination. Disruption of the function of these proteins may generate even lethal outcomes. In this review, we summarize the current knowledge of CA-related studies performed in zebrafish.

The need for a relatively quick solution to the problem of providing highways with roadside service facilities necessitates the development of a series of appropriate standard projects. To increase the efficiency of these series, it is advisable to carry out the interconnection of space-planning solutions based on a particular module. Taking into account the variety of planning and landscape characteristics of the sites for the placement of objects of the mainline service, it seems advisable to choose as a module not a square or rectangular, but a triangular configuration, which allows in most cases to harmoniously block the modules. The proposed roof module in the form of a "regular" triangle facing the tetrahedron has a structural basis in the form of a single-tier rod spatial plate. The principal space-planning solutions of all four dozen objects from the approved nomenclature of the mainline service performed in the process of analyzing the possibilities show the real possibility of solving the development tasks on the basis of this system. The use of the proposed modular system makes it possible to successfully solve a number of tasks to reduce the harmful impact on the environment and effectively use renewable energy sources.

The RNA-guided endonuclease system CRISPR-Cas9 has been extensively modified since its discovery, allowing its capabilities to be extending far beyond double-stranded cleavage to high fidelity insertions, deletions, and single base edits. Such innovations have been possible due to the modular architecture of CRISPR-Cas9 and the robustness of its component parts to modifications and the fusion of new functional elements. Here, we review the broad toolkit of CRISPR-Cas9-based systems now available for diverse genome editing tasks. We provide an overview of their core molecular structure and mechanism and distil the design principles used to engineer their diverse functionalities. We end by looking beyond the biochemistry and towards the societal and ethical challenges that these CRISPR-Cas9 systems face if their transformative capabilities are to be deployed in a safe and acceptable manner.

Evolutionary algorithms and swarm intelligence algorithms find applicability in reinforcement learning of neural networks due to their independence from gradient-based methods. To achieve successful training of neural networks using these algorithms, careful considerations must be made to select appropriate algorithms due to the availability of various algorithmic variations. In Part1, 2 and 3, the author previously reported experimental evaluations on Evolution Strategy, Genetic Algorithm, and Differential Evolution for reinforcement learning of neural networks, utilizing the Acrobot control task. This article constitutes Part4 of the series of comparative research. In this study, Particle Swarm Optimization is adopted as an instance of major swarm intelligence algorithms. The experimental result shows that PSO performed worse than all of DE, GA and ES. The difference between PSO and DE was statistically significant (p<.01). In addition, PSO exhibited lower capability in exploring solutions in high-dimensional search spaces than DE, GA, and ES did. A larger swarm size compensated for the weakness of PSO in global exploration, thus making itself more beneficial than a larger number of swarm search iterations.

In this study, we propose an efficient field-free line (FFL) generator for mechanically driven FFL-magnetic particle imaging (MPI) applications. The novel FFL generator comprises pairs of Halbach arrays and bar magnets. The proposed design generates high-gradient FFLs with low-mass permanent magnets, realizing fine spatial resolutions in MPI. We investigate the generated magnetic field using simulations and experiments. Our results show that the FFL generator yields a high gradient of 4.76 T/m at a cylindrical field of view of 30 mm diameter and a 70 mm open bore. A spatial resolution of less than 3.5 mm was obtained in the mechanically driven FFL-MPI.

Space exploration introduces astronauts to many challenges such as space radiation and microgravity. Researchers have investigated vitamin C as a potential radiation mitigator and antioxidants for sustaining astronaut health. Building on our own studies, which indicate vitamin C's life-saving radioprotective effects and its potential as a radiation mitigator, our research highlights its promise, even when administered 24 h post-exposure. This is particularly relevant in scenarios where astronauts may be exposed to sudden large solar particle events, potentially resulting in lethal doses of space radiation. The success of vegetable cultivation on the International Space Station using NASA's Veggie system offers fresh, vitamin C-rich food. While approved supplements address somatic function, further research is needed to optimize vitamin C's efficacy in humans and develop antioxidant cocktails for space missions. The variable vitamin C content in vegetables underscores the necessity for utilization of artificial intelligence (AI) to assist astronauts in selecting and cultivating vitamin C-rich vegetables that are best suited to combat high levels of space radiation and microgravity. Particularly, AI algorithms can be utilized in analyzing various factors such as nutritional content, growth patterns, and cultivation methods. In conclusion, vitamin C shows significant potential for mitigating space radiation, and ongoing research aims to enhance astronaut health through optimal dietary strategies.

Nanoparticles are of great importance for various scientific and technological applications, drug discovery, ecology, molecular biology, etc. Size is a basic characteristic of any particle, and dynamic light scattering is beyond competition when measuring particle size in dispersions ranging from nanometers to micrometers. Unfortunately, this method has a serious problem in processing and interpreting experimental data. Instrument noise and polydispersity of the sample lead to the situation when one initial autocorrelation function corresponds to several different particle size distributions. Sometimes these different solutions of the inverse task can be found by changing parameters in the software. Sometimes the scientist cannot be suspicious of possible other solutions, having one result from the program. In this article I demonstrate the problem on model and experimental data using three known programs: CONTIN, the Malvern Zetasizer and DynaLS. I also present my own free program Autocor, which allows to test our own hypotheses about the modality and shape of the particle size distribution by optimizing the parameters of our own models with a small number of degrees of freedom.

Efficient energy extraction in photovoltaic (PV) systems relies on the effective implementation of Maximum Power Point Tracking (MPPT) methods. Conventional MPPT techniques often suffer from slow convergence speeds and suboptimal tracking performance, particularly under dynamic variation of environmental conditions. Smart optimization algorithms (SOA) using metaheuristic optimization algorithms can avoid this limitation inherent in the conventional MPPT methods. The problem of slow convergence of the SOA is avoided in this paper using a novel strategy called Swarm Size Reduction (SSR) utilized with Particle Swarm Optimization (PSO) algorithm, specifically designed to achieve short convergence time (CT) while maintaining exceptional tracking accuracy. The novelty of the proposed MPPT method introduced in this paper is the dynamic reduction of the swarm size of the PSO for improved performance of the MPPT of the PV systems. This adaptive reduction approach allows the algorithm to efficiently explore the solution space of PV systems and rapidly exploit to identify the global maximum power point (GMPP) even under fast fluctuation of uneven solar irradiance and temperature. This pioneering ultra-fast MPPT method represents a significant advancement in PV system efficiency and promotes the wider adoption of solar energy as a reliable and sustainable power source. The novel adaptive PSO algorithm also opens new possibilities for further innovations in optimization-driven applications, extending its potential impact on a diverse range of real-world challenges. The results obtained from this proposed strategy are compared with several optimization algorithms to validate its superiority.

The effect of coal hydrophilic particles in water-glycerol drops on the maximum diameter of spreading along a hydrophobic solid surface is experimentally studied by analyzing the velocity of internal flows by Particle Image Velocimetry. The grinding fineness of coal particles was 45-80 μm and 120-140 μm, their concentration was 0.06 wt.% and 1 wt.%. The impact of particle-laden drops on a solid surface occurred at Weber numbers (We) from 30 to 120. It is revealed the interrelated influence of We and the concentration of coal particles on changes in the maximum absolute velocity of internal flows in a drop within the kinetic and spreading phases of the drop-wall impact. A physical model is formulated for internal convective flows in the longitudinal section of a drop parallel to the plane of the solid wall. The kinetic energy of translational motion of coal particles in a spreading drop compensates for the energy expended by the drop on sliding friction along the wall. At We=120, the inertia-driven spreading of the particle-laden drop is mainly determined by the dynamics of the deformable Taylor rim. An increase in We contributes to more noticeable differences in the convection velocities in spreading drops. When the drop spreading diameter rises at the maximum velocity of internal flows, a growth of the maximum spreading diameter occurs. The presence of coal particles causes a general tendency to reduce the drop spreading.

This paper presents research on the application of trajectory design, optimization, and control to an orbital transfer from Mars-Phobos Distant Retrograde Orbits to the surface of Phobos. Given a Distant Retrograde Orbits and a landing location on the surface of Phobos, landing trajectories for which total Δv for a direct 2-burn maneuver is minimized are computed. This is accomplished through the use of Particle Swarm Optimization in which the required Δv and time of flight are optimization parameters. The non-uniform gravitational environment of Phobos is considered in the computation. Results show how direct transfers can be achieved with Δv in the order of ∼30 m/s.

We derive the stabiliser group of the four-vector, also known as Wigner’s little group, in case of massless particle states, as the maximal solvable subgroup of the proper orthochronous Lorentz group of dimension four, known as the Borel subgroup. In the absence of mass, particle states are disentangled into left and right handed chiral states, governed by the maximal solvable subgroups sol2± of order two. Induced Lorentz transformations are constructed and applied to general representations of particle states. Finally, it is argued how the spin-flip contribution is closely related to the occurrence of nonphysical spin operators.

The dynamics of a low-energy charged particle in an axis-symmetric magnetic field is known to be a regular superposition of periodic–although possibly incommensurate–motions. The projection of the particle orbit along the two non-ignorable coordinates (x,y) may be expressed in terms of each other: y=y(x), yet–to our knowledge–such a functional relation has never been directly produced in literature, but only by way of a detour: first, equations of motion are solved, yielding x=x(t),y=y(t), and then one of the two relations is inverted, x(t)→t(x). In this paper we present a closed-form functional relation which allows to express coordinates of the particle’ orbit without the need to pass through the hourly law of motion.

Nanographene oxide (GOn) constitutes a nanomaterial of high value in the biomedical field. However, large scale production of highly stable aqueous dispersions of GOn is yet to be achieved. In this work, we explored high-power ultrasonication as a method to reduce particle size of GO and characterized the impact of the process in the physico-chemical properties of the material. GOn was obtained with lateral dimensions of 99 ±43 nm and surface charge of −39.9 ± 2.2 mV. High-power ultrasonication enabled an improvement of stability features, particularly by resulting in a decrease of the average particle size, as well as zeta potential, in comparison to GO obtained by low-power exfoliation and centrifugation (287 ± 139 nm; −29.7 ± 1.2 mV). Re-markably, GOn aqueous dispersions were stable for up to 6 months of shelf-time, with a global process yield of 74%. This novel method enabled the production of large volumes of highly con-centrated (7.5 mg mL-1) GOn aqueous dispersions. Chemical characterization of GOn allowed the identification of characteristic oxygen functional groups, supporting high-power ultrasonication as a fast, efficient and productive process for reducing GO lateral size, while maintaining the material’s chemical features.

The information entropy for Smoluchowski coagulation equation is proposed based on statistical mechanics. And the normalized particle size distribution is a lognormal function at equilibrium from the principle of maximum entropy and moment constraint. The geometric mean volume and standard deviation in the distribution function are determined as simple constant. The results reveal that the assumption that algebraic mean volume be unit in self-preserving hypothesis is reasonable in some sense. Based on the present definition of information entropy, the Cercignani’s conjecture holds naturally for Smoluchowski coagulation equation. Together with the proof that the conjecture is also true for Boltzmann equation, Cercignani’s conjecture will holds for any two-body collision systems, which will benefit the understanding of Brownian motion and molecule kinematic theory, such as the stability of the dissipative system, and the mathematical theory of convergence to thermodynamic equilibrium.

Radiotherapy using accelerated charged particles is rapidly growing worldwide. About 85% of the cancer patients receiving particle therapy is irradiated with protons, which have physical advantages compared to X-rays but similar biological response. In addition to the ballistic advantages, heavy ions present specific radiobiological features that can make them attractive for treating radioresistant, hypoxic tumors. An ideal heavy ion should have lower toxicity in the entrance channel (normal tissue), and being exquisitely effective in the target region (tumor). Carbon ions have been chosen because they represent the best combination in this direction. Normal tissue toxicities and second cancer risk are similar to those observed in conventional radiotherapy. In the target region, they have increased relative biological effectiveness and reduced oxygen enhancement ratio compared to X-rays. Some radiobiology properties of densely ionizing carbon ions are so distinct from X-rays and protons that they can be considered as a different “drug” in oncology, and may elicit favorable responses such as increased immune response and reduced angiogenesis and metastatic potential. The radiobiological properties of carbon ions should guide patient selection and treatment protocols to achieve optimal clinical results.

Ammonia (NH3), the most prevalent alkaline gas in the atmosphere, plays a significant role in PM2.5 formation, atmospheric chemistry, and new particle formation. This paper reviews quantification of [NH3] through measurements, satellite-remote-sensing, and modeling reported in over 500 publications towards synthesizing current knowledge of [NH3], focusing on spatiotemporal variations, controlling processes, and quantification issues. Most measurements are through regional passive sampler networks. [NH3] hotspots are typically over agricultural regions like the Midwest US and North China Plain, with elevated concentrations reaching monthly averages of 20 and 74 ppbv, respectively. Topographical effects dramatically increase [NH3] over the Indo-Gangetic Plains, North India and San Joaquin Valley, US. Measurements are sparse over oceans, where [NH3] ≈ few tens of ppbv, variations of which can affect aerosol formation. Satellite-remote-sensing (AIRS, CrIS, IASI, TANSO-FTS, TES) provides global [NH3] quantification in the column and at surface since 2002. Modeling is crucial for improving understanding of NH3 chemistry and transport, its spatiotemporal variations, source apportionment, exploring physicochemical mechanisms, and predicting future scenarios. GEOS-Chem (global) and FRAME (UK) models are commonly applied for this. A synergistic approach of measurements↔satellite-inference↔modeling is needed towards improved understanding of atmospheric ammonia, of concern from the standpoint of human health and the ecosystem.

Quantum turbulence deals with the phenomenon of turbulence in quantum fluids, such as superfluid helium and trapped Bose-Einstein condensates (BECs). Although much progress has been made in understanding quantum turbulence, several fundamental questions remain to be answered. In this work, we investigated the entropy of a trapped BEC in several regimes, including equilibrium, small excitations, the onset of turbulence, and a turbulent state. We considered the time evolution when the system is perturbed and let to evolve after the external excitation is turned off. We derived an expression for the entropy consistent with the accessible experimental data, that is, using the assumption that the momentum distribution is well-known. We related the excitation amplitude to different stages of the perturbed system, and we found distinct features of the entropy in each of them. In particular, we observed a sudden increase in the entropy following the establishment of a particle cascade. We argue that entropy and related quantities can be used to investigate and characterize quantum turbulence.

The availability of high quality surface observations of precipitation and volume observations by polarimetric operational radars make it possible to constrain, evaluate and validate numerical models with a wide variety of microphysical schemes. In this article, a novel particle-based Monte-Carlo microphysical model (called “McSnow”) is used to simulate the outer rain bands of Hurricane Dorian which traversed the densely instrumented precipitation research facility operated by NASA at Wallops Island, Virginia. The rain bands showed steady stratiform vertical profiles with radar signature of dendritic growth layers near −15 °C and peak reflectivity in the bright band of 55 dBZ along with polarimetric signatures of wet snow with sizes inferred to exceed 15 mm. A 2D-video disdrometer measured frequent occurrences of large drops &gt;5 mm and combined with an optical array probe the drop size distribution was well-documented in spite of uncertainty for drops &lt;0.5 mm due to high wind gusts and turbulence. The 1D McSnow control run and four numerical “experiments” were conducted and compared with observations. One of the main findings is that even at the moderate rain rate of 10 mm/h collisional breakup is essential for the shape of the drop size distribution.

The COVID-19 pandemic has disrupted the supply chain for personal protective equipment (PPE) for medical professionals, including N95-type respiratory protective masks. To address this shortage, many have looked to the agility and accessibility of additive manufacturing (AM) systems to provide a democratized, decentralized solution to producing respirators with equivalent protection for last-resort measures. However, there are concerns about the viability and safety in deploying this localized download, print, and wear strategy. Several polymer-based AM processes produce porous parts, and inherent process variation between printers and materials also threaten the integrity of tolerances and seals within the printed respirator assembly. The goal of this paper is to quantitatively measure particle transmission through printed respirators of different designs, materials, and AM processes, and assess the viability of printed respirators as N95 equivalents. Results from this study show that respirators printed using desktop/industrial-scale fused filament fabrication processes and industrial-scale powder bed fusion processes have insufficient filtration efficiency at the size of the SARS-CoV-2 virus, even while assuming a perfect seal between the respirator and the user’s face. Almost all printed respirators provided <60% filtration efficiency at the 100-300 nm particle range. Only one respirator, printed on an industrial-scale fused filament fabrication system provided >90% efficiency as-printed. Post-processing procedures including cleaning, sealing surfaces, and reinforcing the filter cap seal generally improved performance, but no respirator sustained the filtration efficiency of an N95 respirator, which filters 95% of SARS-CoV-2 virus particles. Instead, the printed respirators showed similar performance to various cloth masks. While continued optimization of printing process parameters and design tolerances could be implemented to directly print respirators that provide the requisite 95% filtration efficiency, AM processes are not sufficiently reliable for widespread distribution and local production of N95-type respiratory protection without commensurate quality assurance processes in place. Certain design/printer/material combinations may provide sufficient protection for specific users, but the respirators should not be trusted without quantitative filtration efficiency testing. It is currently not advised to expect printed respirators originating from distributed designs to replicate performance across different printers and materials.

This study was aimed at investigating the effects of roasting and cryogenic milling on particle size, water solubility, and amount of bioactive components in ginseng root. Samples were pulverized by cryogenic milling, and one treatment condition was selected for each size range (10-50 μm, and >50 μm). The selected samples were roasted at different temperatures (160-200 °C) followed by cryogenic milling. Powdered samples were analyzed for their physicochemical characteristics. Results revealed that roasted samples exhibited significantly smaller particle size than controls (not roasted, p<0.05), and the particle size of roasted samples decreased with increase in roasting temperature until flocculation occurred around 180-190 °C. With decrease in particle size of ginseng; water solubility index, antioxidant activity, total polyphenol content, and total polysaccharide content were observed to increase. Ginseng samples showed an increasing trend in antioxidant activity with decreasing particle size (p>0.05) with significantly higher values for all roasted samples compared to the controls (p<0.05). Non-polar ginsenosides such as Rg2(S), Rg2(R), Rg3(S), Rg3(R), and Rh1(S) showed an increase in temperature-dependent manner. This study revealed that roasting at certain temperature range with cryogenic milling has positive effects on ginseng by reducing its particle size, and increasing water solubility and bioactive components.

This study aimed to decrease the particle size of ginseng by roasting and cryogenic milling to increase its water solubility and physiological activity. The samples were roasted for different times (9–21 min) and generated in different sizes (10–50, and > 50 μm). All roasted samples revealed significantly smaller particle sizes than did non-roasted samples based on Sauter mean diameter (D [3,2], p < 0.05). Further, the particle sizes of roasted samples decreased till roasting up to 15 min. In terms of the water solubility index (WSI), antioxidant activity, total polyphenol content (TPC), and total polysaccharides according to particle size, 10-20 μm-sized samples showed the highest values when compared with >50 μm-sized samples. Based on roasting time, WSI values of all samples roasted for up to 15 min were higher than those of the control (not roasted) (p < 0.05). Antioxidant activity and TPC also increased with increasing roasting time. Total polysaccharide content was the highest upon roasting for 15 min except for the 10-20 μm sample. Ginsenoside content of roasted samples >20 μm size was higher than that of the control (not roasted) except after 15 min of roasting. Therefore, roasting and cryogenic milling are effective in producing ginseng root powder.

An analysis is presented of the possible existence of a second anomalous dipole moment of Dirac’s particle next to the angular one. It includes a discussion why, in spite of his own derivation, Dirac has doubted about its relevancy. It is shown why since then it has been overlooked and why it has vanished from leading textbooks. A critical survey is given on the reasons of its reject, including the failure of attempts to measure and the perceived violations of time reversal symmetry and chargeparity symmetry. It is emphasized that the anomalous electric dipole moment of the pointlike electron (AEDM) is fundamentally different from the quantum field type electric dipole moment of an electron (eEDM) as defined in the standard model of particle physics and that its measurement requires different instrumentation. A proposal has been described how to prove or disprove its existence by experiment. Moreover, by reference from literature, the possible impact is discussed in the nuclear domain and in the gravitational domain.

Precipitation processes are technologies commonly used in hydrometallurgical plants to recover metals or to treat wastewaters. Moreover, solid-liquid separation technologies, such as thickening or filtering, are relevant unit operations, included in the precipitation technologies. These methods are strongly dependent on the characteristics of the solid precipitates formed during the specific precipitation reaction. One of these characteristics is the particle size distribution (PSD) of the solid precipitates which are fed into a solid-liquid separation process. Therefore, PSD determination is a typical practice for the characterization of the slurries generated in a precipitation plant. Furthermore, the precipitates generated in these processes have a colloidal or aggregation behavior, depending on the operational conditions. Nevertheless, the conventional methods used to estimate PSD (e.g., laser diffraction and/or ciclosizer) have not been designed to measure particles that tend to aggregate or disaggregate, since they include external forces (e.g., centrifugal, agitation, pumping and sonication). These forces affect the true size of the aggregates formed in a unit operation, thereby losing representativity in terms of aggregates particle size. This study presents an alternative method of measuring the size distribution of particles with aggregation behavior, particularly, by using non-invasive microscopy and image processing and analysis. The samples used have been obtained from an experimental precipitation process by applying sulfidization to treat the cyanide-copper complexes contained in a cyanidation solution. This method has been validated with statistical tools and compared with a conventional analysis based on laser diffraction. Our results show significant differences between the methods analyzed, demonstrating that image processing and analysis by microscopy is an excellent and non-invasive alternative to obtaining size distribution of aggregates in precipitation processes.