Impact Of Different Conditions Research Articles

Deep learning based spraying pattern recognition and prediction for electrohydrodynamic system

Effective recognition and prediction of spraying patterns for electrohydrodynamic (EHD) process are extremely important for its applications in high quality micro/nanoparticles preparation, chip coating, droplet-reactor design, and high precision printing, etc. In this study, six distinct spray patterns, namely dripping, spindle, cone-jet, rotational jet, atomization, and skew jet-atomization, were classified through experiments. Subsequently, 30,000 images were obtained to train a convolutional neural network (CNN) model for recognizing EHD spraying patterns, which exhibited a remarkable accuracy of 99.80%. The CNN model was used to recognize the patterns across a range of experimental variables. Dimensionless groups were established and the generalized spraying pattern maps were drawn efficiently via the model. Finally, a database consisting of 11,650 experimental data points was constructed to train a deep neural network (DNN) model, aiming to reduce the number of experiments. The DNN model with an accuracy of 95.88% was employed to predict the spraying patterns, by which a rapid but comprehensive analysis of the impact of different conditions was achieved.

Soil microbial functional profiles of P-cycling reveal drought-induced constraints on P-transformation in a hyper-arid desert ecosystem

Soil water conditions are known to influence soil nutrient availability, but the specific impact of different conditions on soil phosphorus (P) availability through the modulation of P-cycling functional microbial communities in hyper-arid desert ecosystems remains largely unexplored. To address this knowledge gap, we conducted a 3-year pot experiment using a typical desert plant species (Alhagi sparsifolia Shap.) subjected to two water supply levels (25 %–35 % and 65 %–75 % of maximum field capacity, MFC) and four P-supply levels (0, 1, 3, and 5 g P m−2 y−1). Our investigation focused on the soil Hedley-P pool and the four major microbial groups involved in the critical phases of soil microbial P-cycling. The results revealed that the drought (25 %–35 % MFC) and no P-supply treatments reduced soil resin-P and NaHCO3-Pi concentrations by 87.03 % and 93.22 %, respectively, compared to the well-watered (65 %–75 % MFC) and high P-supply (5 g P m−2 y−1) treatments. However, the P-supply treatment resulted in a 12 %–22 % decrease in the soil NH4+-N concentration preferred by microbes compared to the no P-supply treatment. Moreover, the abundance of genes engaged in microbial P-cycling (e.g. gcd and phoD) increased under the drought and no P-supply treatments (p < 0.05), suggesting that increased NH4+-N accumulation under these conditions may stimulate P-solubilizing microbes, thereby promoting the microbial community's investment in resources to enhance the P-cycling potential. Furthermore, the communities of Steroidobacter cummioxidans, Mesorhizobium alhagi, Devosia geojensis, and Ensifer sojae, associated with the major P-cycling genes, were enriched in drought and no or low-P soils. Overall, the drought and no or low-P treatments stimulated microbial communities and gene abundances involved in P-cycling. However, this increase was insufficient to maintain soil P-bioavailability. These findings shed light on the responses and feedback of microbial-mediated P-cycling behaviors in desert ecosystems under three-year drought and soil P-deficiency.

A novel approach for adsorption of organic dyes from aqueous solutions using a sodium alginate/titanium dioxide nanowire doped with zirconium cryogel beads.

The presence of organic dyes in wastewater raises significant environmental and human health concerns, owing to their high toxicity. In light of this, a novel adsorbent material with porous cryogel architecture was developed and employed for the effective removal of organic dyes from an aqueous solution. Initially, a titanium dioxide nanowire doped with zirconium HZTO was synthesized by the hydrothermal process. Subsequently, the beads (SA/HZTO) of sodium alginate and HZTO were successfully prepared through a cross-linking process, employing Ca2+ ions as the crosslinking agent. Structural analysis of SA/HZTO beads was performed using FTIR, SEM, and EDX techniques. We systematically examined the impact of different conditions, including the initial dye concentration, pH, contact time, and adsorbent dosage, on the adsorption process. Batch experiments, both in signal and binary systems, were conducted to rigorously assess the dye adsorption capabilities. Kinetic modeling revealed that the adsorption process adhered to the pseudo-second-order kinetic model. Remarkably, the prepared beads exhibited impressive adsorption capacities of 26 and 29mg/g toward methylene blue (MB) and safranin (SF), respectively. SA/HZTO beads have demonstrated excellent adsorption properties, offering a promising avenue for the development of low-cost, efficient, and reusable adsorbent to remove dyes from wastewater.

Impact of high shear blending on distribution of magnesium stearate on lactose for dry powder inhaled formulations

The use of magnesium stearate along with lactose in Dry Powder Inhaler (DPI) formulations is increasing.The impact of different conditions of high shear blending on the distribution of magnesium stearate on lactose particles was investigated in this study. The formulated blends were manufactured using high shear blending of pre-blended coarse and fine lactose particles with 1.0% (w/w) magnesium stearate under different blending conditions, specifically blending speed and time. The effects of blending conditions on the distribution of magnesium stearate on lactose particles were clearly identifiable by characterizing the formulated blends by means of rheological evaluations, scanning electron microscopy, and chemical surface analysis using time-of-flight secondary ion mass spectrometry (ToF-SIMS). Rheological properties were significantly affected in blends with magnesium stearate compared to blends without magnesium stearate. Blending speed exhibited a strong influence on the distribution of magnesium stearate on lactose surface, while blending time had relatively minor effect.

Utilizing Drone-Based Ground-Penetrating Radar for Crime Investigations in Localizing and Identifying Clandestine Graves.

The decomposition of a body is influenced by burial conditions, making it crucial to understand the impact of different conditions for accurate grave detection. Geophysical techniques using drones have gained popularity in locating clandestine graves, offering non-invasive methods for detecting surface and subsurface irregularities. Ground-penetrating radar (GPR) is an effective technology for identifying potential grave locations without disturbance. This research aimed to prototype a drone system integrating GPR to assist in grave localization and to develop software for data management. Initial experiments compared GPR with other technologies, demonstrating its valuable applicability. It is suitable for various decomposition stages and soil types, although certain soil compositions have limitations. The research used the DJI M600 Pro drone and a drone-based GPR system enhanced by the real-time kinematic (RTK) global positioning system (GPS) for precision and autonomy. Tests with simulated graves and cadavers validated the system's performance, evaluating optimal altitude, speed, and obstacle avoidance techniques. Furthermore, global and local planning algorithms ensured efficient and obstacle-free flight paths. The results highlighted the potential of the drone-based GPR system in locating clandestine graves while minimizing disturbance, contributing to the development of effective tools for forensic investigations and crime scene analysis.

Ti/PbO2 Electrode Efficiency in Catalytic Chloramphenicol Degradation and Its Effect on Antibiotic Resistance Genes.

Livestock farming has led to the rapid accumulation of antibiotic resistance genes in the environment. Chloramphenicol (CAP) was chosen as a model compound to investigate its degradation during electrochemical treatment. Ti/PbO2 electrodes were prepared using electrodeposition. The prepared Ti/PbO2-La electrodes had a denser surface and a more complete PbO2 crystal structure. Ti/PbO2-Co electrodes exhibited improved electrochemical catalytic activity and lifetime in practice. The impact of different conditions on the effectiveness of CAP electrochemical degradation was investigated, and the most favorable conditions were identified (current density: I = 15.0 mA/cm, electrolyte concentration: c = 0.125 mol/L, solution pH = 5). Most importantly, we investigated the effects of the different stages of treatment with CAP solutions on the abundance of resistance genes in natural river substrates (intI1, cmlA, cmle3, and cata2). When CAP was completely degraded (100% TOC removal), no effect on resistance gene abundance was observed in the river substrate; incomplete CAP degradation significantly increased the absolute abundance of resistance genes. This suggests that when treating solutions with antibiotics, they must be completely degraded (100% TOC removal) before discharge into the environment to reduce secondary pollution. This study provides insights into the deep treatment of wastewater containing antibiotics and assesses the environmental impact of the resulting treated wastewater.

Characterization and Prediction of Physical Properties of Luanta Fir Wood with Vacuum Hydrothermal Treatment.

This study used the luanta fir (Cunninghamia konishii Hayata) wood, one of the most used wood construction and building materials in Taiwan, as specimens to examine the impact of different conditions of vacuum hydrothermal (VH) treatment on the physical properties of this wood. A prediction model for these properties was created using a nondestructive spectroscopy technique. The test results revealed that the mass loss, moisture exclusion efficiency, anti-swelling efficiency, color difference, and surface contact angle of the VH-treated wood all increased under increasing heat treatment temperature and time. Moreover, the use of near-infrared (NIR) spectroscopy in creating the prediction model for the physical properties of the VH-treated luanta fir wood revealed that the ratios of performance to deviation (RPD) for mass loss, equilibrium moisture content, and color difference were all above 2.5, indicating a high prediction accuracy. These results suggested that an NIR spectrometer can serve as a useful instrument for the accurate prediction of the physical properties or for controlling the quality of VH-treated wood.

Methodological analysis of personalization in urban recommender systems by distance measures

Citizens increasingly rely on urban recommender systems (URS’s) to plan daily activities in the physical urban world. Nonetheless, there is a growing concern that personalization in URS’s enforce urban filter bubbles. Existing research on this topic is still limited, especially methodologically. One problem is the use of a limited set of distance measures for analyzing differences between item sets returned by URS’s under different conditions. Another problem is the lack of advanced analysis models for investigating and comparing the relative impact of different conditions on returned item sets. In this paper, we explore the use of different set distance and geospatial distance measures and multivariate distance matrix regression (MDMR) to assess the relative impact of different determinants of item sets. The analysis of data collected from Google Maps yielded more nuanced conclusions about filter bubbles and personalization when geospatial distance measures were used. Also, search language rather than search location is found to dominantly predict which items URS’s return.

The Impact of Different Conditions on Protease Hydrolysis for Gliadin Degradation

The Impact of Different Conditions on Protease Hydrolysis for Gliadin Degradation

Mechanistic understanding of metal-catalyzed oxidation of polysorbate 80 and monoclonal antibody in biotherapeutic formulations

Surfactants are commonly used in biotherapeutic formulations to prevent the formation of aggregates and protect proteins from denaturation. Among them polysorbates are the most widely used. However, they are known to be prone to degradation, mainly via enzymatic hydrolysis and oxidation.In this study, the impact of different conditions and factors on the oxidation of polysorbate 80 (PS80) and of a monoclonal antibody (mAb) was evaluated. In particular, the role of different formulation components (e.g., mAb concentration, pH, buffer, surfactant grade, chelators) was investigated in the presence of iron as transition metal contaminant.The results of our studies demonstrated that PS80 oxidation was accelerated even in the presence of iron levels as low as 20 ppb. In addition, the results showed that the oxidation of a specific solvent-exposed mAb methionine increased with PS80 oxidation, in particular under accelerated stress conditions and that the oxidation phenomenon was hindered in absence of iron or after addition of EDTA. Our results showed that PS80 “all oleate” (PS80-AO) was more sensitive to oxidative degradation than PS80 “multi-compendial” (PS80-MC). Contrary to acetate and citrate buffers, the results showed that the kinetics of PS80 oxidation was pH-dependent in presence of histidine buffer. It was also demonstrated that, when increasing its concentration, the mAb exhibited a protective effect against metal catalyzed PS80 and methionine oxidation.Our systematic studies on the role of the formulation components and potential contaminants (i.e., iron) demonstrated the complexity of the oxidative mechanism and the importance of different competitive systems, including pro-oxidant factors (e.g., iron, pH, PS80 quality) and antioxidant factors (e.g., protein concentration, EDTA, citrate) that may occur in biologic formulations containing PS80.

Degradation Assessment of Natural Stone Claddings over Their Service Life: Comparison between Tehran (Iran) and Lisbon (Portugal)

Now more than ever, the construction sector is aiming to adopt more sustainable solutions. To achieve this purpose, more durable solutions must be adopted, making rational decisions at the design and maintenance stages regarding the conditions of environmental exposure and use. In this sense, knowledge regarding the service life of building components is crucial. This knowledge should not be a general concept, or a standard value, and adapting practices from one country to another is extremely challenging. In this sense, this study analyses the service life of natural stone claddings. We adopt a methodology initially proposed for Lisbon (Portugal), intending to evaluate its applicability to other geographical contexts, in order to perform a more reliable service life prediction of stone claddings located in Tehran (Iran). An estimated service life of 65 years was obtained for a sample of 162 stone claddings directly adhered to the substrate, located in Tehran, which were analysed by in situ inspections. The impact of different conditions (e.g., type of stone and environmental exposure conditions) on the service life of stone claddings in Tehran was quantified, which revealed that the exposure to environmental agents, such as wind, rain and pollutants, is the main cause of degradation of the natural stone claddings.

Methylene blue uptake by gum arabic/acrylic amide/3-allyloxy-2-hydroxy-1-propanesulfonic acid sodium salt semi-IPN hydrogel

In this study, the capacity of methylene blue (MB) uptake from aqueous solution was investigated using acrylic amide-co-3-Allyloxy-2-hydroxy-1-propanesulfonic acid sodium salt/Gum Arabic semi-IPN hydrogel. The semi-IPN hydrogels were prepared by the classical free radical solution technique. The swelling experiments were carried out gravimetrically and the swelling kinetics parameters were calculated. Fourier transform infrared spectroscopy (FTIR) and scanning electron microscope (SEM) confirmed the semi-IPN hydrogel formation. The MB uptake was studied by the batch technique and the impact of different conditions was investigated. It was found that the obtained semi-IPN hydrogels gave adsorption capacity for the dye within a range of 101–187 mg g−1 at the initial dye concentration of 100 mg/L. The adsorption kinetics (pseudo-first-order and pseudo-second-order) and the adsorption isotherms (Langmuir, Freundlich, and Temkin equations) were tested and the adsorption data was well described by the pseudo-second-order and Freundlich models, respectively. The maximum adsorption capacity calculated by the Langmuir model (R2 = 0.8718) was 655.2 mg g−1. The thermodynamic study indicated the spontaneity and the endothermic nature of MB adsorption. Furthermore, the usability study showed that the prepared adsorbents could be employed repeatedly for successive 5 cycles of adsorption and desorption.

Electro-Hydraulic Proportional Position Control Using Auto Disturbance Rejection Based on RBF Neural Network

Large friction force and large dead zone are two typical nonlinear characteristics of electro-hydraulic proportional valve controlled hydraulic cylinder position control system. Aiming at those characteristics, a dead zone dynamic compensation algorithm is researched in order to reduce the lag time and control error. At the same time, a control strategy of radial basis function (RBF) neural network combined with auto disturbance rejection control (ADRC) is researched according to the impact of different conditions. The experimental result shows that the proposed algorithm improves performance of the electro-hydraulic proportional valve controlled hydraulic cylinder position control system. In positioning control experiment, the overshoot is 0 and the stability error is 0. In tracking control experiment, the lag time is reduced from the original 1.5 s to 0.2 s with no flat top phenomenon and the maximum error was reduced from 20 mm to 3 mm.

Accelerated in vitro release testing method for a long-acting peptide-PLGA formulation

Poly (lactic-co-glycolic acid) (PLGA), a biocompatible and biodegradable polymer, is one of the most commonly used vehicles for controlled-release (CR) implantable dosage forms. Drug molecules formulated in such CR vehicles are released slowly over an extended period of time – often months to years – posing challenges for batch release and quality control testing. Thus, reliable and reproducible accelerated testing methods are required to bridge this gap during early formulation development. This work describes the development of an accelerated in vitro release testing method to predict the real-time in vitro release of a synthetic peptide from a 6-month CR PLGA implant formulation. While accelerated methods have been previously reported for PLGA-based formulations, this work describes a unique case of an aggregation-prone peptide, which required careful attention to the impact of different conditions on both release kinetics and peptide stability. This method describes a suitable combination of release conditions that could help in understanding the release profiles of such peptides prone to aggregation. Parameters including pH, buffer species, temperature, and addition of organic co-solvents and surfactants were evaluated separately and in combination for their ability to achieve complete peptide release within 2 weeks while accurately recapitulating release rate, profile and peptide stability. The accelerated release method that gave the best agreement with real-time release was a mixed media of co-solvent (5% tetrahydrofuran), surfactant (5% TritonX-100) and elevated temperature (50 °C) in a neutral buffer (PBS pH 7.4). This optimized accelerated release method achieved complete release of the peptide load within 14–21 days compared to 3- to 6-months of real-time release and could discriminate critical differences in release behavior between different CR formulations to guide formulation and process development.

Seismic Performance of a Long-Span Cable-Stayed Bridge under Spatially Varying Bidirectional Spectrum-Compatible Ground Motions

Considering the socioeconomic prominence of long-span cable-stayed bridges, it is important to ensure their normal operation after strong earthquake events. To this end, their seismic performance must be based on a proper understanding of the relationship between structural capacity and seismic demand. However, evaluating the seismic demands on cable-stayed bridges is challenging due to relatively long distances between supports and the complex composition of various structural elements. The large dimension in the horizontal direction inevitably leads to incoherent input ground motions at supports, while various structural components such as cables, decks, and pylons make it difficult to define the system’s performance limit-state or capacity using a single index or function. This work presents three main contributions to properly assess the seismic performance of a long-span cable-stayed bridge. First, an algorithm was proposed to generate a set of bidirectional spectrum-compatible ground motions for the multiple supports of a bridge. Second, two performance measures were proposed to quantitatively assess the seismic demands and capacity of a cable-stayed bridge: probabilistic comparison index and axial force-bending moment (PM) safety factor. Third, the impacts of the seismic motions on the long-span cable-stayed bridge were thoroughly examined using eight different scenarios in terms of the three aspects: (1) multisupport excitation, (2) assumed soil class, and (3) wave passage effect. For this purpose, the Incheon Grand Bridge was chosen as a reference structure. This bridge has a central span of 800 m and a total length of 1,480 m. The results demonstrate that the seismic demands of the long-span cable-stayed bridge vary along with different conditions of seismic motions, and the proposed performance measures and ground motion-generating algorithm enable quantitative investigation of the impact of different conditions on the long-span cable-stayed bridge.

The “force” of cloxacillin residue will be with you in various dairy products – The last experimental evidence

In the present study, the transfer of one of the most widely used antibiotics in dairy cows, cloxacillin, from raw milk to a wide range of dairy products such as yoghurt, kefir, milk curd, cream, rennet cheese, whey, butter, buttermilk, milk powder and whey powder was investigated. Raw milk was fortified with cloxacillin at three different concentration levels: 15 and 30 μg/kg, which correspond of 0.5 and 1 cloxacillin maximum residue level (MRL) and 100 μg/kg. Spiked milk was used to produce 10 different dairy products, according to typical industrial processes. All obtained dairy products were analysed to determine the cloxacillin residues in order to measure the degree of cloxacillin degradation, concentration factor and retention rate during the various treatments. Additionally, the impact of different conditions of storage (in the refrigeration and freezing) on the stability of cloxacillin in the obtained dairy products were tested. The dairy product manufacturing processes were unaffected by the presence of cloxacillin. The cloxacillin residues were determined in all dairy products obtained during 4 different experiments. The highest concentration factor was observed in whey powder (10.0) and milk powder (5.0). The highest reduction in the cloxacillin residual level was observed in yoghurt (35 ± 4%). The lowest amounts of cloxacillin, ranging from 7 to 20%, were transferred to cream, butter, rennet cheese and buttermilk, the highest retention rate was observed for whey (85 ± 4%). In general, the results obtained from this study reveal that stability of cloxacillin in most cases was affected (the relative responses at a range of 45–87%), with the exception of yoghurt, milk powder and whey powder, regardless of storage conditions, the relative response was ≥90%. In most cases, the degradation was about 20%, which indicates that consumers can still be exposed to cloxacillin residues. The dark side of the results showed that the use of milk contaminated with cloxacillin in the dairy industry could affect the safety of dairy products, since most of the investigated industrial processes do not eliminate this antibiotic residue.

Relevansi Slippery Slope Theory Ditinjau Dari Perspektif Gender Wajib Pajak

This study aims to reveal the potential causes of the phenomenon of increasing taxpayer compliance in Bali which was previously very difficult to achieve. This study examines the relevance of the slippery slope theory in terms of taxpayer's gender perspective through testing the impact of different conditions of taxpayer trusts and tax authorities on mandatory compliance tax, and the impact of gender differences on taxpayer behavior in certain conditions of trust and power, which also affects the level of tax compliance. This research was carried out by using the experimental method with a 2x2x1 design. The experimental participants consisted of taxpayers who were purposive sampling selected, which were then grouped into four main groups based on treatment variables and gender. Further data analysis will be carried out quantitatively using the two-way analysis of variance (ANOVA) method. The results of this study indicate that taxpayers’ trust in the tax authority is the most important factor in encouraging taxpayers’ compliance to pay taxes voluntarily, and is able to suppress individual opportunist behavior caused by gender differences of the taxpayers

Impact of different conditions of breath-holding on the results of renal artery Doppler sonography: A pilot study.

To investigate the impact of different breath-holding conditions on the results of renal artery Doppler ultrasonography (RADS). In 45 healthy volunteers, we performed RADS examination during breath-holding while breathing naturally and after a deep inspiration. We measured and compared peak systolic flow velocity (PSV), end diastolic velocity (EDV), and resistance index (RI) of the right (RRA) and left (LRA) renal artery, and PSV, EDV, RI, acceleration time and acceleration index (AI) of the right and left interlobar arteries. The RRA and LRA PSV were, respectively, 76 ± 13 cm/s and 77 ± 15 cm/s under natural breathing and 93 ± 18 cm/s and 89 ± 24 cm/s after deep inspiration (P ≤ .001). The RRA and LRA EDV were also greater at deep inspiration (P < .001 and P = .019, respectively). There was no significant difference in RRA or LRA RI. The PSV, RI, and AI of the right and left interlobar arteries were greater after deep inspiration (P ≤ .001), without difference in AI. Breath-holding conditions may influence Doppler measurements of renal artery flow velocity and should be reported and taken into account.

A Robust Active Safety Enhancement Strategy With Learning Mechanism in Vehicular Networks

Driving safety has been a hot topic in recent vehicular research. However, research on active control strategy, by which an accident might be avoided before it really happens, is still lacking, especially those appealing to machine learning methods with real traffic data. In addition, previous works constructed models with only one or a few factors considered, while the impact of multiple factors on a collision probability is overlooked. In this paper, based on machine learning methods with an actual traffic dataset, we propose a multi-level active safety control strategy taking the Multi-source, Multi-parameter, and Multi-purpose (3M) properties of an accident into consideration. First, by analyzing the impact of different conditions on an accident with the AHP (Analytic Hierarchy Process)-Ridge regression and bisecting K-means clustering model, the safety inter-vehicle distance is derived by learning from an actual traffic dataset. Besides, ELM(Extreme Learning Machines) is adopted as a verification scheme for safety distance calculation. Subsequently, we design a three-level active safety control scheme using the LQG (Linear Quadratic Gaussian) optimal-control model based on the obtained safety inter-vehicle distance. Numerical results show that by comparing with some classical braking and car-following models, our strategy can always keep the distance of two followed vehicles at a safety state. To further explore the impact of the time complexity on the rear-end collisions, we also implemented a road-test and verified that our model can timely respond to the risks and keep two cars always in safety.

Theory-choice, transient diversity and the efficiency of scientific inquiry

Recent studies of scientific interaction based on agent-based models (ABMs) suggest that a crucial factor conducive to efficient inquiry is what Zollman (2010) has dubbed ‘transient diversity’. It signifies a process in which a community engages in parallel exploration of rivaling theories lasting sufficiently long for the community to identify the best theory and to converge on it. But what exactly generates transient diversity? And is transient diversity a decisive factor when it comes to the efficiency of inquiry? In this paper we examine the impact of different conditions on the efficiency of inquiry, as well as the relation between diversity and efficiency. This includes certain diversity-generating mechanisms previously proposed in the literature (such as different social networks and cautious decision-making), as well as some factors that have so far been neglected (such as evaluations underlying theory-choice performed by scientists). This study is obtained via an argumentation-based ABM (Borg et al. 2017, 2018). Our results suggest that cautious decision-making does not always have a significant impact on the efficiency of inquiry while different evaluations underlying theory-choice and different social networks do. Moreover, we find a correlation between diversity and a successful performance of agents only under specific conditions, which indicates that transient diversity is sometimes not the primary factor responsible for efficiency. Altogether, when comparing our results to those obtained by structurally different ABMs based on Zollman’s work, the impact of specific factors on efficiency of inquiry, as well as the role of transient diversity in achieving efficiency, appear to be highly dependent on the underlying model.