Intermediate Process Research Articles

The Financial Accelerator, Wages, and Optimal Monetary Policy

This paper studies the effects of labor market outcomes on firms’ loan demand and on credit intermediation. In a first step, I investigate how wages in the production sector affect bank net worth and the process of financial intermediation in partial equilibrium. Second, the role of the identified channels are studied in general equilibrium using a new- Keynesian DSGE-model with financial frictions and an endogenous financial accelerator mechanism. Third, I investigate how perfect and imperfect labor markets, in a setting with interactions between production factor costs and the intermediation of credit, affect the transmission mechanism of monetary policy. The analysis reveals that financial frictions reduce the factor demand elasticity of capital to a change in wages. This finding is relevant for the determination of optimal monetary policy, both for financial shocks and supply shocks inflation stabilization imposes high welfare costs. At the same time, stabilizing nominal wages becomes welfare beneficial by reducing both the volatility of the credit spread and the output gap.

Mathematical estimation for maximum flow of goods within a cross-dock to reduce inventory.

Supply chain management has recently renovated its strategy by implementing a cross-docking scheme. Cross-docking is a calculated logistics strategy where freight emptied from inbound vehicles is handled straightforwardly onto outbound vehicles, eliminating the intermediate storage process. The cross-docking approach thrives on the minimum storage time of goods in the inventory. Most of the cross-docks avail temporary storage docks where items can be stored for up to 24 hours before being packed up for transportation. The storage capacity of the cross-dock varies depending on the nature of ownership. In the rented cross-docks center, the temporary storage docks are considered of infinite capacity. This study believes that the temporary storage facilities owned by the cross-dock center are of finite capacity, which subsequently affects the waiting time of the goods. The flow rate of goods within the cross-docks is expected to be maximum to avoid long waiting for goods in the queue. This paper uses a series of max-flow algorithms, namely Ford Fulkerson, Edmond Karp, and Dinic's, to optimize the flow of goods between the inbound port and the outbound dock and present a logical explanation to reduce the waiting time of the trucks. A numerical example is analyzed to prove the efficacity of the algorithm in finding maximum flow. The result demonstrates that Dinic's algorithm performs better than the Ford Fulkerson and Edmond Karp algorithm at addressing the problem of maximum flow at the cross-dock. The algorithm effectively provided the best result regarding iteration and time complexity. In addition, it also suggested the bottleneck paths of the network in determining the maximum flow.

Modelling and statistical analysis of the intermediate laser remelting regime by moving average filtering

Surface polishing by laser remelting (SP-LRM) is a novel surface finishing technology that is characterized by rapidity, versatility, repeatability as well as the lack of material removal. SP-LRM can be implemented in several thermodynamic regimes whose presence depends on a complex combination of power-speed-focus-trajectory-material parameters. The intermediate LRM regime exhibits the most desirable surface topography smoothening along with predictability, controllability, and minimum bulging. The experimental observations of the intermediate LRM process have demonstrated the reliable applicability of a moving average filter for modeling and statistical analysis of the surface formation. The obtained results have enabled the identification and classification of the LRM process regimes (shallow-LRM, intermediate-LRM, and deep-LRM) through the optimization of a filter window corresponding to a maximum correlation coefficient found between actual and modelled remelted surface profiles along the LRM track. The proposed statistical modelling of the LRM-based surface formation opens up new research directions for model-based self-optimization and self-control of the SP-LRM process.

Study on the wetting behavior between oil droplets and kaolinite substrate based on interaction force measurement and high-speed dynamic visualization

The basic principle of static wetting has been studied in depth, but the dynamic wetting mechanism, especially partially wetting, is still not well understood. In this work, the high-speed dynamic visualization method was used to study the partially wetting dynamics behavior of a millimeter-scale oleic acid droplet (referred to as oil droplet here) on the kaolinite substrate. On the other hand, a macroscopic force measurement technology was adopted to measure directly the wetting force of oil droplet-kaolinite surface during the interaction between a millimeter-scale oil droplet and the kaolinite substrate. The former showed that the spreading process of an oil droplet on the surface of kaolinite could be divided into three sub-processes: the early linear rapid spreading process dominated by inertial force, the intermediate exponential slow spreading process dominated by viscous force, and the long-time spreading process tending to equilibrium state. The latter indicated that the oil droplet-kaolinite wetting force measured by the microbalance could be related to the change in the system free energy during the spreading of an oil droplet on the kaolinite substrate, and theoretical analysis suggested that the change of system free energy during the spreading of droplets on the solid surface could be estimated based on experimental measurable parameters, and the surface wettability was the dominant factor determining the wetting force at a given droplet. These findings can provide fundamental understanding regarding the partial wetting mechanism and provide guidance for studying the interaction between liquid droplets and solid surfaces from the perspective of interaction force.

Design of an EEG analytical methodology for the analysis and interpretation of cerebral connectivity signals

The objective of this study is to design an Electroencephalographic (EEG) analytic methodology that allows to develop a variety of analysis and interpretations of brain signals. The initial phase considers the acquisition and filtering of EEG signals, the division into bands in data ranges, and the storage of EEG signals in a cloud data base. Then, an analytical phase considering descriptive, predictive and prescriptive analysis is accomplished. A sequence of analytic intermediate processing steps is done in order to render a graphic visualization of significant correlations between pairs of EEG channels. Pearson correlation is utilized to detect synchronic connectivity through the brain areas. Time series in nearly instantaneous time lapses are treated by using Hilbert Huang Transform. An experimental design by submitting a set of students to an abbreviated version Raven visual test is made providing results in correlation maps of cerebral connectivity.

Surface characterization of a modified cold work tool steel treated by powder‐pack boronizing

AbstractThe present work examines the effects of pack‐boronizing treatment on the surface characteristics of modified industrial cold‐work tool steel intended for polymer crushing. Particular attention is paid to optimizing the process parameters to improve the tool surface properties and thus achieve a satisfactory tool life. To this end, a series of samples were subjected to boronizing treatment within the temperature range from 800 °C to 1000 °C for soaking periods of 2 h, 4 h, 6 h and 8 h. The structural and mechanical properties of the modified metal surface were analyzed using optical and scanning electron microscopy, x‐ray diffraction, microhardness testing and pin‐on‐disk tribotesting. The adhesion quality of the boride layer‐substrate was carried out using the adhesion test Daimler Benz Rockwell‐C. The corrosion properties were determined by the electrochemical polarization method. Experimental results showed that the optimum temperature‐temporal conditions of 900 °C/4 h that are the intermediate processing parameters led to a better compromise between the intended properties, in terms of resistance to wear and corrosion, as well as adhesion quality.

Восприятие изобразительного текста: проблематизация, актуализация, новые методологические подходы

The problems of perception of various types and formats of texts that have been formed over a long historical period and are rapidly transforming into the digital and the coming post-digital era are in the research focus of a number of humanities disciplines. It is texts and their perception that are today an actual research platform for solving the fundamental scientific problem of modern communication. This article actualizes and problematizes the question of the nature and perception of visual content, which is becoming urgent today, forming the paradigm of the so-called visual research. The stated problem is considered taking into account its interdisciplinarity and the factors that have determined the strengthening of visuality in modern conditions. The article analyzes the discussions that have been going on since the second half of the twentieth century about visuality and visualization, as well as about the peculiarities of the perception of pictorial texts, the specifics of which in a particular era are determined by (1) historically conditioned visual and cultural norms, perceptual models that are formed under the influence of semiosociopsychological factors of modernity, (2) topics, the arsenal of supra-temporal universal constant perception structures formed in the centuries-old practice of human interaction with pictorial sign systems. The authors pay special attention to visual narrative - a generic concept of isocontent. Without claiming to fully characterize it, they highlight, based on existing research, the paradigm of its definitions, the features of its functioning and perception. The emphasis is placed on the uniqueness of visual language and visual thinking, on the internal verbality of the pictorial text, on its semiotic codes and semantic connectives, as well as on the transformations of the language of the visual narrative in the process of its perception. The transformations are reduced to a simultaneous and interrelated process of receiving a polycode text in two languages - verbal and visual - at once. Having analyzed different approaches to the pictorial text and its perception, the authors infer that, with a certain unity of views on the nature of the pictorial text and its reception, there are different opinions on the problem of its “regulation”: from the complete rejection of any interference with the skills and abilities of the “art of seeing” (reading visual text) to the development of specific teaching methods of such art. In conclusion, the article emphasizes that, for all their importance, it is not so much the author’s strategies for creating pictorial texts that are in a strong position, but rather the background knowledge (cultural memory) of recipients, their experience of communication with isocontent (the level of mastery of visual code, reading visual narrative, decoding pictorial texts and their transcoding, for example, in verbal text; finally, interpretation skills acquired in the intermediate processes of perception of iso-content of different types and formats) - all this, according to the authors of the article, not only allows competent management, but also needs it. The authors declare no conflicts of interests.

Segmentation and Measurement of Superalloy Microstructure Based on Improved Nonlocal Block

The microstructure of superalloy materials has a decisive impact on its service performance. When preparing the material and photographing the microstructure, different depths of metallography perpendicular to the cut plane appear in the microstructure image. These metallographic features are major factors causing inaccurate segmentation. Aiming at the problems of traditional image processing methods, such as large noise and poor robustness of the edge extraction, the deep learning method is introduced. The receptive field of the traditional convolutional neural network method is too local to obtain remote dependencies, and dense feature extraction also brings problems such as excessive noise. To address the problem of non-tangential metallographic information in microstructure images that is not easily distinguishable. We consider how to combine and utilize the feature maps of the intermediate process as effectively as possible, and find that reusing affinity matrices from different angles and stacking them can improve the overall effect, and can solve the problem of inaccurate segmentation of metallographic images at different depths. We propose to improve and optimize the non-local attention module and further combine the module with the UNet network to form a new improved SNL-Unet image segmentation structure, which significantly raises the accuracy and efficiency of image segmentation, Additionally, we measure the characteristic parameters such as volume fraction, average thickness and the degree of rafting. The code for this paper will be available at github.com/ustbjdl1021/improved-snl-unet.

Fuzzy Image Enhancement Method based on a New Intensifier Operator

In recent years, fuzzy image enhancement methods have been widely applied in image enhancement, which generally consists of three steps: fuzzification, modify membership(using intensifier (INT) operator), and defuzzification. This paper proposed a new INT operator used in fuzzy image enhancement. The INT operator is adjustable for different test images. The image enhancement method is as follows, firstly, calculate the image threshold (T ) using the OTSU method. Secondly, calculate pivotal point p corresponding to T , and find the corresponding INT operator function. Finally, use the INT operator in fuzzy Image Enhancement. The INT operator is used multiple times in the image processing process to obtain multiple result images. Comparative experiments show that the proposed new INT operator has better image enhancement effect when INT operator is applied at the same number of times. On the other hand, more intermediate process result images can also be obtained through the proposed new INT operator. More result images can provide material resources for the subsequent image processing.

Optimization of the Everolimus Intermediate Preparation Process: Impurity Identification Followed by One-Pot Transformation to the Desired Product

An investigation of the everolimus intermediate PG-EVR preparation process resulted in the identification of three impurities PG-D,E,F constantly formed as byproducts in large amounts. Their structures were reliably established based on two-dimensional (2D) NMR and liquid chromatography–high-resolution tandem mass spectrometry (LC–HRMS/MS) data as dialkylated rapamycin derivatives. Finding that one of these impurities PG-E is hydrolyzable to the target everolimus intermediate resulted in optimized technology based on changing the selectivity of byproduct formation to PG-E as the major one followed by its one-pot quantitative transformation to PG-EVR. The yield of the everolimus intermediate increased by 10% under mild conditions, while lower amounts of reagents and solvents were required. The active pharmaceutical ingredient (API) that meets the requirements of the European Pharmacopoeia was prepared from thus obtained intermediate with no need for high-performance liquid chromatography (HPLC) purification, indicating a significant increase in the efficiency of large-scale production using new technology.

Microalgae-based bioplastics: Future solution towards mitigation of plastic wastes

Global demand for plastic materials has severely harm the environment and marine sea life. Therefore, bioplastics have emerged as an environmentally friendly alternative due to sustainability, minimal carbon footprint, less toxicity and high degradability. This review highlights the sustainable and environmentally friendly approach towards bioplastic production by utilizing microalgae as a feed source in several ways. First, the microalgae biomass obtained through the biorefinery approach can be processed into PHA under certain nutrient limitations. Additionally, microalgae biomass can act as potential filler and reinforcement towards the enhancement of bioplastic either blending with conventional bioplastic or synthetic polymer. The downstream processing of microalgae via suitable extraction and pre-treatment of bioactive compounds such as lipids and cellulose are found to be promising for the production of bioplastics. Moving on, the intermediate processing of bioplastic via lactic acid synthesized from microalgae has favoured the microwave-assisted synthesis of polylactic acid due to cost efficiency, minimum solvent usage, low energy consumption, and fast rate of reaction. Moreover, the reliability and effectiveness of microalgae-based bioplastics are further evaluated in terms of techno-economic analysis and degradation mechanism. Future improvement and recommendations are listed towards proper genetic modification of algae strains, large-scale biofilm technology, low-cost cultivation medium, and novel avocado seed-microalgae bioplastic blend.

Monocular 3D Object Detection Based on Uncertainty Prediction of Keypoints

Three-dimensional (3D) object detection is an important task in the field of machine vision, in which the detection of 3D objects using monocular vision is even more challenging. We observe that most of the existing monocular methods focus on the design of the feature extraction framework or embedded geometric constraints, but ignore the possible errors in the intermediate process of the detection pipeline. These errors may be further amplified in the subsequent processes. After exploring the existing detection framework of keypoints, we find that the accuracy of keypoints prediction will seriously affect the solution of 3D object position. Therefore, we propose a novel keypoints uncertainty prediction network (KUP-Net) for monocular 3D object detection. In this work, we design an uncertainty prediction module to characterize the uncertainty that exists in keypoint prediction. Then, the uncertainty is used for joint optimization with object position. In addition, we adopt position-encoding to assist the uncertainty prediction, and use a timing coefficient to optimize the learning process. The experiments on our detector are conducted on the KITTI benchmark. For the two levels of easy and moderate, we achieve accuracy of 17.26 and 11.78 in AP3D, and achieve accuracy of 23.59 and 16.63 in APBEV, which are higher than the latest method KM3D.

Efficiency and productivity of the Brazilian banks: A new approach based on two-stage network DEA

This article creates a conceptual model, called a network system, to represent the Brazilian banking production system, based on its internal operational processes. The first, called the intermediation process, measures a bank's efficiency in extending loans from its available resources. The second, called the revenue process, measures a bank's efficiency in earning profit, mainly from loans granted. We adopt a two-stage DEA model. In the first stage, a relational network DEA model measures both the network system efficiency scores and internal processes. This technique, associated with the Malmquist Index, assesses performance changes over time. In the second stage, these efficiency scores are considered dependent variables, such that Tobit models can determine how the Brazilian credit market's characteristics can explain the network system and internal processes' efficiency. Results show not only a growing trend toward greater efficiency in the revenue process, but also an increase in productivity accompanied by a decline in the intermediation process technology. Given the high banking spreads in Brazil, these results indicate deterioration in the quality of the credit portfolio and the prospect of future insolvency. We discuss implications of this scenario for domestic banks and collateral policy.

From Chatter to Action: How Social Networks Inform and Motivate in Rural Uganda

AbstractFrom public health to political campaigns, numerous attempts to encourage behavior begin with the spread of information. Of course, seeding new information does not guarantee action, especially when it is difficult for receivers to verify this information. We use a novel design that introduced valuable, actionable information in rural Uganda and reveals the intermediate process that led many in the village to hear the information but only some to act on it. We find that the seeded information spread easily through word of mouth via a simple contagion process. However, acting on the information spread less easily; this process relied instead on endogenously created social information that served to vet, verify, and pass judgment. Our results highlight an important wedge between information that a policy intervention can best control and the behavior that ultimately results.

Analysis of three-body charmed B -meson decays under the factorization-assisted topological-amplitude approach

We analyze the quasi-two-body charmed $B$ decays ${B}_{(s)}^{+,0}\ensuremath{\rightarrow}{D}_{(s)}^{*}{P}_{2}\ensuremath{\rightarrow}{D}_{(s)}{P}_{1}{P}_{2}$ with ${P}_{1,2}$ as a pion or kaon. The intermediate processes ${B}_{(s)}\ensuremath{\rightarrow}{D}_{(s)}^{*}{P}_{2}$ are calculated with the factorization-assisted topological-amplitude approach, and the resonant effects are calculated with the Breit-Wigner formalism. Taking all $P$-wave resonance states ${\overline{D}}_{(s)}^{*}$ into consideration, we present the related branching fractions, calculate the Breit-Wigner-tail effects, and investigate the flavor $SU(3)$ breaking effects. Most of our branching fractions are consistent with the perturbative QCD approach's predictions as well as the current experimental data. With more precision calculation of the intermediate two-body charmed $B$-meson decays, our quasi-two-body $B$ decays calculation has significantly less theoretical uncertainty than the perturbative QCD approach. Many of those channels without any experimental data will be confronted with the future more accurate experiment measurements. Our results of the Breit-Wigner-tail effects also agree with the experimental data very well. In ${B}^{0}$ decays, this effect can reach approximately to 5%. It is also found that the Breit-Wigner tail effects are not sensitive to the widths of their corresponding resonances.

Evidence from the Changing Carbon Isotopic of Kerogen, Oil, and Gas during Hydrous Pyrolysis from Pinghu Formation, the Xihu Sag, East China Sea Basin

Semi-open hydrous pyrolysis experiments on coal-measure source rocks in the Xihu Sag were conducted to investigate the carbon isotope evolution of kerogen, bitumen, generated expelled oil, and gases with increasing thermal maturity. Seven corresponding experiments were conducted at 335 °C, 360 °C, 400 °C, 455 °C, 480 °C, 525 °C, and 575 °C, while other experimental factors, such as the heating time and rate, lithostatic and hydrodynamic pressures, and columnar original samples were kept the same. The results show that the simulated temperatures were positive for the measured vitrinite reflectance (Ro), with a correlation coefficient (R2) of 0.9861. With increasing temperatures, lower maturity, maturity, higher maturity, and post-maturity stages occurred at simulated temperatures (Ts) of 335–360 °C, 360–400 °C, 400–480 °C, and 480–575 °C, respectively. The increasing gas hydrocarbons with increasing temperature reflected the higher gas potential. Moreover, the carbon isotopes of kerogen, bitumen, expelled oil, and gases were associated with increased temperatures; among gases, methane was the most sensitive to maturity. Ignoring the intermediate reaction process, the thermal evolution process can be summarized as kerogen0(original) + bitumen0(original)→kerogenr (residual kerogen) + expelled oil (generated) + bitumenn+r (generated + residual) + C2+(generated + residual) + CH4(generated). Among these, bitumen, expelled oil, and C2-5 acted as reactants and products, whereas kerogen and methane were the reactants and products, respectively. Furthermore, the order of the carbon isotopes during the thermal evolution process was identified as: δ13C1 < 13C2-5 < δ13Cexpelled oil < δ13Cbitumen < δ13Ckerogen. Thus, the reaction and production mechanisms of carbon isotopes can be obtained based on their changing degree and yields in kerogen, bitumen, expelled oil, and gases. Furthermore, combining the analysis of the geochemical characteristics of the Pinghu Formation coal–oil-type gas in actual strata with these pyrolysis experiments, it was identified that this area also had substantial development potential. Therefore, this study provides theoretical support and guidance for the formation mechanism and exploration of oil and gas based on changing carbon isotopes.

Application of integrated factor evaluation–analytic hierarchy process–T-S fuzzy fault tree analysis in reliability allocation of industrial robot systems

Aiming at the defects (only two kinds of state, i.e., normal or fault) of existed reliability allocation methods without considering the intermediate degradation process, a methodology named integrated factor evaluation–analytic hierarchy process–T-S fuzzy fault tree analysis (IFE-AHP-T-S fuzzy FTA) is proposed to allocate the reliability index of industrial robot systems (IRSs) which have multiple fault states. Firstly, the reliability model of IRSs is established and the allocation principle of reliability index is discussed. Secondly, two-layer IFE model is established considering the degradation of mechanical structure and multi-state fault of IRSs to evaluate the technical merit of different subsystems. The hesitant fuzzy language set is adopted to reduce the subjectivity of expert evaluation process, which have the ability of dealing with uncertain information. Then, the AHP is proposed to allocate different weights for influence factors, and the T-S fuzzy FTA is presented to calculate fault probability and mean time between failures (MTBF) in the process of weight allocation of reliability index for IRSs and six subsystems. Finally, multi-state reliability index allocation of IRSs is completed. This investigation has a significance for reducing the fault probability and unsafe factors, and provides a theoretical basis for the whole life cycle design of IRSs.

Intermediate‐variable‐based Kalman filter for linear time‐varying systems with unknown inputs

AbstractThis article proposes a systematic design methodology of unknown input estimation for time‐varying systems in which unknown inputs exist in system dynamic and measurement simultaneously. By introducing intermediate variables, the relationship between unknown inputs and system states is modeled by an intermediate dynamic process, and then a modified Kalman filter is designed to estimate system states and unknown inputs. Moreover, the stability condition is derived such that the mean square error of the intermediate Kalman filter is bounded. An illustrative example is employed to demonstrate the effectiveness of the proposed methods.

Functionally Assessing the Age-Related Decline in the Detection Rate of Photons by Cone Photoreceptors.

Age-related decline in visual perception is usually attributed to optical factors of the eye and neural factors. However, the detection of light by cones converting light into neural signals is a crucial intermediate processing step of vision. Interestingly, a novel functional approach can evaluate many aspects of the visual system including the detection of photons by cones. This approach was used to investigate the underlying cause of age-related visual decline and found that the detection rate of cones was considerably affected with healthy aging. This functional test enabling to evaluate the detection of photons by cones could be particularly useful to screen for retinal pathologies affecting cones such as age-related macular degeneration. However, the paradigm used to functionally measure the detection of photons was complex as it was evaluating many other properties of the visual system. The aim of the current mini review is to clarify the underlying rationale of functionally evaluating the detection of photons by cones, describe a simpler approach to evaluate it, and review the impact of aging on the detection rate of cones.

Degradation dynamics of quantum dots in white LED applications

Quantum Dots (QDs) are being investigated in a hybrid white light LED structure which inculcates phosphor in the package with a blue LED chip as the light source recently. In this work, Zn doped CdS QD with ZnS shell together with green light emission phosphor is used. Upon prolonged operation, degradation of the LEDs due to the degradation of QDs is observed, which can limit its practical applications. The degradation includes intensity reduction as well as blue shift of the emitted wavelength from the white light. Three stages of degradation are observed, namely an enhancement state where light intensity is found to increase, followed by a rapid degradation stage where light intensity decreases rapidly, and finally a slower degradation stage where the degradation rate of light intensity slows down and continues till the end of the test. Through various detail material analysis, with confirmation from the density functional theory (DFT) calculations, we find that the degradation of the LEDs is due to the time evolving degradation of CdS core structure, beginning from the oxidation of sulfur vacancy of CdS QDs by the nearby oxygen atoms as a result of imperfection of the ZnS protective coating around the QDs in the presence of blue light. This oxidation renders a transformation of CdS into CdO at the initial stage. The final stage is the formation of CdSO4 via some intermediate processes.