Exhaustive Process Research Articles

The Importance of the Listed Buildings Resurvey in England (1982–1989)

ABSTRACT The National Heritage List for England represents a remarkable case where a state, normally relied upon for healthcare, policing, defence and infrastructure, turned its hand to architectural history. ‘Listed’ buildings in England are legally protected from demolition or alteration without permission. The list itself is valuable for the study of architecture and often constitutes the only writing about buildings. It is also an important milestone in the history of heritage management. This paper argues that the most important event in the history of the list, after its origin, was the ‘accelerated resurvey’ between 1982 and 1989. This was the first and last time listing was approached as an exhaustive and systematic process; the list doubled in size during the short period of the resurvey. This paper is the second on the subject, the first being by Martin Robertson and others who were directly involved in the project shortly after it was completed, over 30 years ago. This paper presents a critical reassessment of the resurvey process, from an author not involved in the project. The paper pays particular focus on the practicalities of the resurvey (how it was done) and the criteria of the resurvey (how buildings were selected).

PENGARUH PENAMBAHAN UNSUR TEMBAGA PADA PENGECORAN TEKAN BLOK SILINDER BEKAS TERHADAP NILAI IMPAK DAN KEAUSAN

The cylinder liner block is part of the cylinder block which functions as a place for the engine working process to take place. Where in this section the suction, compression, work and exhaust processes occur. Cylinder blocks have two types, some can be repaired and cannot be repaired, to utilize cylinder blocks that cannot be repaired by recycling them by casting metal with copper (Cu) with variations in the addition of 5%, 10%, 15% with a casting temperature of 1150⁰C using metal molds using the press technique method. Data collection was carried out by wear testing, impact testing, and microstructure testing. By increasing the percentage of copper (Cu) in the cylinder block casting, the highest wear was obtained with the addition of 15% Cu of 2,87×10-9 m3. The highest impact strength of 15% Cu is 0.12 Joule/mm2.

Deep Learning for Fast and Reliable Initial Access in AI-Driven 6G mmWave Networks

We present DeepIA, a deep neural network (DNN) framework for fast and reliable initial access (IA) for artificial intelligence (AI)-driven 6G millimeter wave (mmWave) networks. DeepIA reduces the beam sweep time compared to a conventional exhaustive search-based IA process by utilizing only a subset of the available beams. DeepIA maps received signal strengths (RSSs) obtained from a subset of beams to the beam that is best oriented to the receiver. In both line of sight (LoS) and non-line of sight (NLoS) conditions, DeepIA reduces the IA time and outperforms the conventional IA&#x0027;s beam prediction accuracy. We show that DeepIA&#x0027;s accuracy saturates with the number of beams used, and also depends on the particular choice of the beams used. The choice of beams that are selected is consequential and improves accuracy by upto upto <inline-formula><tex-math notation="LaTeX">$35\%$</tex-math></inline-formula> and <inline-formula><tex-math notation="LaTeX">$70\%$</tex-math></inline-formula> in NLoS and LoS channels. We find that, averaging multiple RSS snapshots further reduces the number of beams needed and achieves more than <inline-formula><tex-math notation="LaTeX">$95\%$</tex-math></inline-formula> accuracy in both LoS and NLoS conditions. We introduce interference into our models to understand impact on performance. Finally, we evaluate the beam prediction time of DeepIA through embedded hardware implementation and show the improvement over the baseline approach.

Chaotic Analysis of the Reversible Pump Turbine Exhaust Process in Pump Mode Based on a Data-driven Method

Due to the important strategic position of Pumped Storage Power Plants (PSPP) in global energy upgrading, conducting in-depth research on the various operating conditions of pump turbine units is important for their safe and stable operation. This study sought to clarify the gas–liquid phase motion and the nonlinear chaotic characteristics of the process of exhaust and pressurization in pump mode; with the simplified objective model proposed here, a visualization of the process is achieved using data-driven methods, and the nonlinear characteristics of gas–liquid phase motion during the process are theoretically demonstrated. A method that combines data-driven and chaotic analysis is proposed to qualitatively and quantitatively analyze the force and torque time-series signals of the runner under different exhaust rates. The results indicate that the chaotic characteristics of the force signals and torque signals of the runner are not in a single linear relationship with the exhaust rates. Therefore, this research also provides guidance on exhaust rates with the aim of informing actual engineering practice, the purpose of which is to reduce the vibration amplitude caused by repetitive torque and improve the stability of the unit operations.

Modeling the Process of Critical Exhaustion of Oxygen in a River Caused by Exponential Source of Pollution

The analysis and improvement of the river's change dynamics are critical to the global investigation of water quality issues. This study investigates the mathematical model representation of one dimension of a pair of advection-dispersion equations. These equations pertain to the concentrations of both pollutants and dissolved oxygen. Certain terms, which demonstrate an increase in the decay rate of pollution through exponential sources and assume a decreasing river's cross-sectional measurement, lead to the diminished oxygen levels observed in this study. The crucial points are demonstrated using both analytical and numerical analysis of the steady-state model, which allows for examining multiple situations about the elimination of oxygen and aquatic survival in a river with severe pollution.

MitoTempo treatment as an approach to cure persistent viral infections?

Chronic viral infections are characterized by exhausted virus-specific T cells. Exhaustion is associated with mitochondrial dysfunction, revealing a possible target for treatment. Targeting these metabolic processes may interfere with the exhaustion process of immune cells during infection. It has been shown that the mitochondria-targeted antioxidant MitoTempo could restore hepatitis-B-virus-specific T cells in vitro. Thus, we investigated MitoTempo as a treatment option using the chronic lymphocytic choriomeningitis virus (LCMVcl13) mouse model.MitoTempo treatment of chronically LCMVcl13 infected mice resulted in a transient reduction of LCMV titer. However, no obvious restoration of functional LCMV-specific T cells was observed, beside subtle changes in phenotype of GP33- and NP205-specific T cells. However, these changes did not translate into significantly more functional responses.Our study showed a transient antiviral effect of MitoTempo, but no profound effect on exhausted T cell responses, although further studies are needed to further elucidate the mechanism and use of MitoTempo.

A systematic approach for identifying unique genomic sequences for Fusarium oxysporum f. sp. lactucae race 1 and development of molecular diagnostic tools

Fusarium oxysporum f. sp. lactucae (FOLac) is a soil- and seedborne fungal pathogen that causes Fusarium wilt of lettuce, an important disease threatening global lettuce production. Based on pathogenicity on differential lettuce cultivars, four races (1-4) have been identified, with race 1 the only race detected in the United States, and the closely related, emerging race 4 known only in Europe. The development of race-specific diagnostic tools is hindered by insufficient genomic data to distinguish between the two races and FOLac from other F. oxysporum formae speciales and nonpathogenic isolates. Here, we describe a systematic approach for developing diagnostic markers for FOLac race 1 that utilized a comprehensive sequence database of F. oxysporum to identify 15 unique genomic sequences. Marker specificity was validated through an exhaustive screening process against genomic data from 797 F. oxysporum isolates representing 64 formae speciales and various plants and non-plant substrates. One of the unique sequences was used to develop a TaqMan quantitative polymerase chain reaction assay and a recombinase polymerase amplification assay, both exhibiting 100% sensitivity and specificity when tested against purified DNA from 171 F. oxysporum isolates and 69 lettuce samples. The relationship between qPCR Ct values and colony forming units (CFU)/g values was also determined. This study not only introduces a new marker for FOLac race 1 diagnostics and soil quantitation, but also underscores the value of an extensive genomic database and screening software pipeline for developing molecular diagnostics for F. oxysporum formae speciales and other fungal taxa.

Abstract A047: Activation of conventional type 2 dendritic cells (cDC2) by anti-CD47 may enhance antitumor T cell function in mouse liver cancer models

Abstract Anti-CD47 has been extensively studied for its effects on activating phagocytosis by blocking the ‘don’t eat me’ signal presented by CD47 expressed on cancer cells. This study explored the effects of anti-CD47 on enhancing antigen presentation by dendritic cells and improving antigen-specific antitumor immunity. Mouse Hepa1-6 liver cancer cells with or without over-expression of LCMV-GP protein and splenocytes from P14 transgenic mice were used to test antigen-specific antitumor immunity. Bone marrow-derived conventional type 1 and type 2 dendritic cells (cDC1 and cDC2) or MutuDC1/ DC2 cell lines were co-cultured with CD8 T cells with or without exhaustion. Effects of anti-CD47 on the cross-priming ability of DC were analyzed by T cell proliferation (CSFE labeling), activation (expression of IFNγ, granzyme B, TNFa, and IL-2), cell killing (in vitro cytotoxicity assay) and T cell exhaustion (LAG3, TOX, PD1 expression). In vivo studies indicated that anti-CD47 treatment may suppress tumor growth, activate intra-tumoral cDC2 but not type 1 dendritic cells (cDC1), and delay CD8 T cells from entering terminal exhaustion in the tumor microenvironments. In vitro studies indicated that anti-CD47 may enhance the priming ability of cDC2, but not cDC1, and increase ISG15 expression in cDC2. When co-cultured with exhausted T cells, anti-CD47-treated cDC2 may delay the exhaustion process and restore antigen-specific effector function and cytotoxic capacity. Conclusion: Anti-CD47 may enhance antitumor T cell function in mouse liver cancer models by activation of cDC2, which may serve as a new strategy of developing immunotherapeutic agents for liver cancer (supported by grants NSTC 111- 2314-B-002-039 and 113-2314-B-002-113-MY3). Citation Format: Cheng-Zhe Jian, Da-Liang Ou, Chia-Lang Hsu, Chien-Kuo Lee, Chiun Hsu. Activation of conventional type 2 dendritic cells (cDC2) by anti-CD47 may enhance antitumor T cell function in mouse liver cancer models [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Tumor Immunology and Immunotherapy; 2024 Oct 18-21; Boston, MA. Philadelphia (PA): AACR; Cancer Immunol Res 2024;12(10 Suppl):Abstract nr A047.

Design and optimization of the exhaust system for an aviation piston engine

Abstract To further enhance the performance of an aviation piston engine, an engine performance simulation analysis model was constructed by using GT-Power software to design improvements to its exhaust system. The impacts of different exhaust system schemes on the exhaust process, the in-cylinder combustion, and the heat release process at a cruising speed of 5500 RPM were analyzed. Based on the results, under cruising speed conditions, a new exhaust system was designed for the engine by referring to the structural form of a resonant exhaust system. The D-optimal Latin hypercube sampling method was used to obtain sample data for the experimental design of the structural parameters of the designed exhaust system. The response surface approximation models characterizing power and fuel consumption rate were established by using the least squares method. The significance of the impact of each structural parameter on engine performance was analyzed through a multifactor analysis of variance. The key structural parameters of the designed exhaust system were then subjected to multi-objective optimization. The results indicate that at 5500 RPM, the designed exhaust system can increase engine power by 2.88%; after optimization, engine power can be further increased by 3.15%, and the fuel consumption rate is reduced by 4.07%.

Evaluation of Prognostic Factors in Adult Chemical Corneal Injury.

The aim of this study was to evaluate prognostic factors that may be useful in predicting final visual acuity in patients admitted to the clinic with chemical corneal injuries. Data on age, sex, time to admission, irrigation solutions (balanced salt solution or phosphate buffered saline) and type of substance causing chemical injury were recorded. On admission, all patients were evaluated according to Roper Hall and Dua classifications. At the twelfth month after treatment, all measurements were repeated. A total of 131 patients with chemical corneal injuries [group 1 (acid, n = 73) and group 2 (alkaline, n = 58)] were included. The initial best corrected visual acuity (BCVA) level was "20/40 and above" in 32 patients (43.8%) in group 1 and 14 patients (24.1%) in group 2. According to Roper Hall classification, the mean grade was 1.92 ± 0.9 in group 1 and 2.27 ± 1.1 in group 2. According to Dua classification, the mean grade of the patients in group 1 was 2.16 ± 0.9 and 2.58 ± 1.2 in group 2. Posttreatment BCVA level improved to "1/200 to 19/200" in 8 (66.7%) of the patients with an initial BCVA level of "perception of light or hand movements." In univariate analysis, initial visual acuity and posttreatment visual acuity were statistically significant (P < 0.001). It was also statistically significant in multivariate analysis adjusted for sex and age (P < 0.001). In conclusion, the treatment of chemical corneal injuries is a long and exhausting process. The use of initial visual acuity and Dua classification in prognosis prediction may provide high success.

An Enhanced Approach to Intelligent Computer-Assisted Localization of Liver Tumor on Computed Tomography Images

Computed Tomography (CT) Imaging is frequently used to find liver cancer. CT imaging of the liver generates cross-sectional images of the abdominal region. The task of segmenting a liver tumor on CT images is tedious due to the anatomic complexity of the liver. Therefore, liver tumor detection has been performed manually or semi-automatically which is an exhaustive process. Further, a tumor may be present on only some slices of the CT scan and hence there is a need to automatically identify images that contain tumors from acquired CT images and then locate a region of the tumor on those images for further diagnosis. Automatic detection helps the radiologist to obtain fast, accurate, and effective results. Accordingly, in this paper, an enhanced approach is proposed based on deep learning, efficient fuzzy c-means (EFCM) clustering, and a region-based algorithm for the detection of a liver tumor. A deep learning model built on a convolutional neural network is used to identify whether the CT image contains a tumor. If it contains the tumor, then the proposed EFCM and region-based algorithms are applied to locate the tumor on the CT image. The EFCM algorithm is combined with a region-based technique to automatically determine the initial pixel and threshold values required to segment the liver tumor. The proposed method is applied to several CT abdominal images. The results of the tumor segmentation are validated by comparing them with the tumor regions detected by radiologists. The estimated results of the experiment show that the proposed technique successfully detects the liver tumor on the CT image with less than 2% relative error.

Prediction of parameters in the Ibarra–Medina–Krawinkler model for reinforced concrete columns using random forest and active learning

The lumped plasticity model is widely used in the practical modeling of reinforced concrete (RC) columns because of its computational efficiency. However, existing formulations for estimating the backbone curve and cyclic deterioration parameters often fail to accurately predict new data with high variability and necessitate laborious calibrations. To address it, a machine-learning (ML) approach utilizing the random forest (RF) algorithm to predict seven parameters in the Ibarra–Medina–Krawinkler lumped plasticity model for depicting hysteretic response is proposed in this study, where a comprehensive data of 475 RC columns, encompassing diverse material properties, geometric features, and failure modes, is used. In addition, an active-learning framework is integrated to address the limited availability of labeled data in supervised ML tasks, which reduces the exhausted labeling process. The proposed RF surpasses existing research and commonly used ML models regarding coefficient of determination. Additionally, the predicted parameters more accurately simulate the behavior of strength and stiffness degradation in the hysteretic loop of columns than empirical regression formulas. These results will benefit the high-fidelity seismic risk assessments of RC buildings.

Thermoelectric properties enhancement and optimization of SnTe-based material with single doping: RSM-ANN approach

Tin Telluride (SnTe) stands out among semiconductor materials, drawing attention as an environmentally friendly alternative to conventional Lead Telluride (PbTe). This study explores the novel incorporation of titanium (Ti) and zirconium (Zr) as dopant elements in SnTe-based materials, an approach that has never been previously investigated. Leveraging mathematical modeling and machine learning methodologies, we use Response Surface Methodology (RSM) and Artificial Neural Network-Genetic Algorithm (ANN-GA) to predict thermoelectric properties of SnTe-based materials and find the optimum dopant element addition and operating temperature. Eleven samples featuring varying Ti and Zr concentrations are employed in experimental investigations, with dopant amounts ranging from 0 to 0.05 M. Characterization of each sample is conducted across a temperature spectrum from 50 to 450 °C, yielding a comprehensive dataset of 99 entries for neural network model construction. The generated RSM and ANN models demonstrate remarkable predictive accuracy for the thermoelectric properties of SnTe-based materials, showcasing coefficient of determination (R2) values spanning from 0.986 to 0.998. This study uses RSM and ANN-GA to predict an optimized zT value of 0.558. This value surpasses the highest zT value from the experiment by 3.33 %. In conclusion, this investigation underscores the potency of RSM and ANN as valuable tools for advancing research on SnTe-based thermoelectric materials, exemplifying their capacity to hasten the exhausting process of finding the optimum dopant addition and operating temperature.

A hybrid cyber–physical risk identification method for grid-connected photovoltaic systems

Identifying risks in modern electric power systems is essential, and one of the main difficulties concerns covering the wide range of technologies that permeate its cyber and physical domains. Different risk identification methods have been proposed, but applying them individually does not guarantee coverage of both domains. On the other hand, the simple non-articulated application of a set of existing risk identification methods can lead to an exhaustive and inefficient process. This paper proposes a new Cyber–Physical Risks Identification Method (CPRIM) to comprehensively and efficiently identify risks in electrical power systems. To systematically cover risks ranging from the cyber domain to the physical domain, CPRIM combines in a complimentary and articulated way the National Institute of Standards and Technology (NIST) Cybersecurity Framework, a Risk Factor model, and the HAZOP, establishing a novel hybrid risk identification approach. This work also proposes a method based on Jaccard and overlap indexes to quantitatively assess the complementarity and superposition that may exist when applying different risk identification methods to electrical power systems. The results obtained in a real computer-managed photovoltaic plant indicate that CPRIM can efficiently identify cyber–physical risks, showing a reasonable trade-off between system coverage and redundancy in identified risks.

Network pharmacology combined with experimental validation reveals the mechanism of action of cangerzisan on allergic rhinitis

Ethnopharmacological relevanceAllergic rhinitis (AR) stands as a non-infectious inflammatory condition affecting the nasal mucosa, marked by bouts of sneezing, nasal itching, and congestion. This ailment afflicts individuals across all age groups and poses challenges for effective treatment due to its chronic nature. Cangerzisan (CEZS), documented in the Jishengfang compendium, represents a traditional Chinese medicinal formula long utilized for AR management.Aim of the study: Investigating mechanism beneath therapeutic effect of CEZS in alleviating AR. Materials and methodsThe main active components in CEZS were determined by High Performance Liquid Chromatography (HPLC).The active constituents of CEZS and their corresponding targets were identified through an exhaustive screening process employing TCMSP database. To identify targets relevant to AR, GeneCards, OMIM, and DisGeNET databases were thoroughly applied. Protein-protein interaction (PPI) network was assembled utilizing STRING platform. Potential signaling pathways influenced by CEZS were delineated through GO and KEGG enrichment analyses. Subsequently, an AR model was induced by administering aluminum hydroxide (Al(OH)3) and ovalbumin (OVA) for affecting basal and local sensitization, respectively, facilitating experimental validation of the principal signaling pathways. ResultsThere were 61 active constituents identified within CEZS, targeting a pool of 129 entities associated with AR treatment. Pathways analysis of KEGG revealed that CEZS potentially inhibits AR advancement via modulating TLR4 signaling pathway. Animal experiments demonstrated that CEZS effectively alleviated symptom scores in guinea pigs with AR. Moreover, it exhibited notable improvements in serum immune and inflammatory factors levels, as well as reduced inflammatory infiltration within nasal mucosa, including goblet and mast cells. CEZS was found to enhance GATA-3 expression while reducing T-bet expression, thereby modulating the TH1/TH2 immune balance. Additionally, CEZS downregulated HMGB1, TLR4, and p–NF–κB/NF-κB protein expressions within nasal mucosa of guinea pigs. ConclusionsThe therapeutic mechanism of CEZS against AR involves rectifying TH1/TH2 immune imbalance and upregulating inflammatory and immune factors through modulating key proteins expression within TLR4 pathway. This targeted regulation effectively impedes AR progression.

Techno economic and life cycle assessment of olefin production through CO2 hydrogenation within the power-to-X concept

The paper deals with exhaustive process modelling, techno-economic and life cycle assessment (TEA/LCA) of olefin (ethylene and propylene) production through captured CO2 and electrolytic hydrogen. Olefins are important building block chemicals with several applications and carbon capture and utilisation (CCU) can provide a sustainable production route. The proposed system involves direct air capture (DAC) of CO2; proton exchange membrane (PEM) water electrolysis for hydrogen production, methanol synthesis, methanol to olefins (MTO) upgrade, and power generation from off-shore wind turbines. This study proposes a new integrated process as the first attempt to holistically assess a whole CCU assembly aiming at olefins production. Processing modelling has been implemented using the Aspen plus V12.1 and MATLAB R2022a software to solve the mass and energy balances of each unit operation. The modelling results showed a carbon efficiency of 72.3% to ethylene and propylene. In addition, the process is designed and integrated in such a way that no external heat supply is required. A specific energy consumption (SEC) of 150 MJ/kg olefins (41 kWh/kg) has been estimated. A minimum selling price of £3.67 per kg of olefins is required for the proposed process to break-even. The sensitivity analysis has revealed that the major cost driver is the cost of electricity. In addition, the life cycle assessment (LCA) has exposed that the proposed synthesis route of olefins has the potential to reduce the global warming potential (GWP) by 47% compared to fossil - based production. The outcomes of this study can be beneficial to engineering conceptual studies, policy makers and contribute new information to the CCU academic community.

The Effect of Education Performed Using Mobile Application on Supportive Care Needs and Quality of Life in Women with Breast Cancer: Randomized Controlled Trial

ObjectivesAimed to determine the effect of education provided with a mobile application on the supportive care needs and quality of life of women undergoing breast-conserving surgery. MethodsThe study was conducted in 81 patients. The experimental group received mobile application and the control group received standard education. Fisher's Exact Test, Chi-Square test, Student's t Test, Mann-Whitney U test, mixed design analysis of variance and Bonferroni-Dunn test were used to analyze the data. ResultsWhile the pre-study supportive care needs scores of the women were similar in the experimental (85.37 ± 23.58) and control (83.13 ± 23.03) groups, they decreased significantly in the experimental group at the 4th and 8th-week measurements (54.34 ± 27.28; 58.78 ± 16.51) (p < .05). In the 4th and 8th week measurements, the quality of life of the experimental group (72.26 ± 14.12; 71.04 ± 8.12) increased significantly, while no significant change was found in the control group (42.50 ± 14.38; 45.63 ± 8.28). ConclusionsIt was found that the supportive care needs of the decreased and their quality of life increased after the education given to women with a mobile application. Implications for Nursing PracticeThis study ensured that women who had a sufficiently intense and exhausting process during the cancer treatment process could comfortably receive care support and education with the mobile application at any time and place they wanted. It also revealed that nurses can provide care and education support to their patients at any time and place they want with the mobile application in their busy work tempo.

A small team as an effective group and center of leadership

Building an ideal small team capable of solving problems that are beyond the capacity of an ordinary group of specialists is a long and exhausting process. This article presents the ability to work in a small team as the most valuable personality trait. Describing the small team philosophy as highly effective, the author of the article presents it as a reference model of gifted and talented individuals, a well-coordinated combat unit, a special centre of leadership, flexibility and psychological compatibility. Revealing the effectiveness of a small team in the symbolic range of two images of “Simplicity”-“Complexity”, the author derives the symbolic rule of “Simplicity”: the effectiveness of success is rooted in the ability to work only with small teams of smart people. It is proved that as soon as the number of people in a team increases, “Complexity” is automatically introduced. The article also describes the philosophy of a two-person team. It is proved how much more effective, constructive and motivated it can be compared to a large team. It is highlighted that the key to the success of a two-person team is the holistic dominance of five components: 1) psychological safety; 2) reliability; 3) structure and clarity; 4) awareness; 5) influence. It is found out that a small team is a homogeneous combat unit, since it is designed to promote the origination of a new, emergent mind, the need for which increases significantly in the conditions of high danger, constant change and uncertainty. The author emphasises that the coordinated work of a small team in a dangerous environment requires rapid adaptability, constant reassessment of the situation, discussion and coordination. In such a team, its members, sending signals to each other every minute, decoding the responses, should understand every step and intention of their partner, as this is the key to life and victory.

범죄피해상담사의 대리외상 경험에 관한 내러티브 탐구

This study is the Qualitative Research on the experience of vicarious trauma of crime victim counselors. This study was conducted on three crime victim counselors who have been active for more than 10 years according to the narrative inquiry method. According to the participants’ experiences and episodes, the study results were reconstructed in the aspects of: “accidentally begin,” “passionately immersed,” “get confused and dazed,” “standing at a deadlock,” “conflict just got experienced,” “pain now shared,” and “stepping into growth.” The discussion according to the research results is given as follows. First, the vicarious trauma experience of the crime-victim counselor was exhaustion in terms of physical, cognitive, emotional, and relational aspects. Second, the proxy trauma process of crime-victim counselors was shown to be similar to the adaptation and exhaustion process of counselors adapting to new areas of expertise. Third, overcoming vicarious trauma of crime-victim counselors has turned out to be an experience of enhancing their expertise and also of establishing identity as a crime-victim counselor by accepting the limitations of their intervention and strengthening the capabilities as a therapist. As this study is the one of the narrative inquiries that aims to inquire the fundamental meaning and nature of the vicarious trauma experience that most crime-victim counselors suffer from, so, the aim of this study is to comprehend the vicarious trauma experience of the crime-victim counselors who have experienced during their counseling.

Color Biomimetics in Textile Design: Reproduction of Natural Plant Colors through Instrumental Colorant Formulation.

This paper explores the intersection of colorimetry and biomimetics in textile design, focusing on mimicking natural plant colors in dyed textiles via instrumental colorant formulation. The experimental work was conducted with two polyester substrates dyed with disperse dyes using the exhaustion process. Textiles dyed with different dye colors and concentrations were measured in a spectrophotometer and a database was created in Datacolor Match Textile software version 2.4.1 (0) with the samples' colorimetric properties. Colorant recipe formulation encompassed the definition and measurement of the pattern colors (along four defined natural plants), the selection of the colorants, and the software calculation of the recipes. After textile dyeing with the lowest expected CIELAB color difference (ΔE*) value recipe for each pattern color, a comparative analysis was conducted by spectral reflectance and visual assessment. Scanning electron microscopy and white light interferometry were also used to characterize the surface of the natural elements. Samples dyed with the formulated recipe attained good chromatic similarity with the respective natural plants' colors, and the majority of the samples presented ΔE* between 1.5 and 4.0. Additionally, recipe optimization can also be conducted based on the colorimetric evaluation. This research contributes a design framework for biomimicking colors in textile design, establishing a systematic method based on colorimetry and color theory that enables the reproduction of nature's color palette through the effective use of colorants.