Desired Results Research Articles

Tribological Behavior of Friction Materials Containing Aluminum Anodizing Waste Obtained by Different Industrial Drying Processes

With sustainability dominating the industry, recycling the generated waste from different processes is becoming increasingly important. This study focuses on recycling waste generated during aluminum anodizing waste (AAW) in friction material formulations for automotive braking applications. However, before utilization, the waste needs to be pre-treated, which mainly involves drying. Hence, four different industrial drying methods were studied to dry the AAW, and the corresponding characteristics were observed by evaluating its residual humidity and crushability index. The waste powders were further characterized using FT-IR and SEM/EDXS to understand their constituents. The initial analysis showed that the waste subjected to the drying process P2 and P1 with the lowest final humidity fetched the most desirable results, with P1 having the simpler drying procedure. The AAW powders were added in a commercial friction material formulation at 6 and 12 wt.% and subjected to friction, wear, and non-exhaust particulate matter analysis. The worn surfaces were analyzed using SEM/EDXS evaluation to understand the extension and composition of the deposited secondary contact plateaus. It was seen that the 12 wt.% addition of waste processed using the P1 technique provided the most satisfactory friction, wear, and emission characteristics, along with expansive secondary contact plateaus with a good contribution of the waste in its formation. This study showed a good relationship between the processing method and a formulation’s tribological and emission characteristics, thereby paving the way for using this drying method for other waste requiring pre-treatment.

Rapid detection of endogenous impurities in walnuts using near-infrared hyperspectral imaging technology

Impurities in walnut-based products pose a significant risk to human health, necessitating the development of rapid and efficient methods for detecting endogenous impurities in walnut shell-breaking materials. To address this issue, this study aims to investigate the feasibility of near-infrared hyperspectral imaging (NIR-HSI) in conjunction with conventional chemometric methods and deep learning models. First, biochemical experiments demonstrated differences in the total phenolic and flavonoid contents of different walnut kernels. An improved support vector machine model based on the butterfly optimization algorithm was constructed for classification using an NIR dataset of endogenous impurities in walnuts, achieving an accuracy of 96.12 %. In addition, this study proposed the WT-NIRSNet model, a deep neural network with an additional attention mechanism, and compared it to a traditional chemometric approach. The study demonstrated an accuracy of 99.03 % on the test set using WT-NIRSNet to solve the fast classification problem of endogenous impurities in walnuts. It can achieve desirable classification results using only raw spectral data without complex preprocessing operations and is superior to traditional chemometric models. Therefore, the NIR-HSI technique combined with deep neural networks has a significant potential for detecting endogenous impurities in walnuts.

Convergence analysis of a second order numerical scheme for the Flory–Huggins–Cahn–Hilliard–Navier–Stokes system

We present an optimal rate convergence analysis for a second order accurate in time, fully discrete finite difference scheme for the Cahn–Hilliard–Navier–Stokes (CHNS) system, combined with logarithmic Flory–Huggins energy potential. The numerical scheme has been recently proposed, and the positivity-preserving property of the logarithmic arguments, as well as the total energy stability, have been theoretically justified. In this paper, we rigorously prove second order convergence of the proposed numerical scheme, in both time and space. Since the CHNS is a coupled system, the standard ℓ∞(0,T;ℓ2)∩ℓ2(0,T;Hh2) error estimate could not be easily derived, due to the lack of regularity to control the numerical error associated with the coupled terms. Instead, the ℓ∞(0,T;Hh1)∩ℓ2(0,T;Hh3) error analysis for the phase variable and the ℓ∞(0,T;ℓ2) analysis for the velocity vector, which shares the same regularity as the energy estimate, is more suitable to pass through the nonlinear analysis for the error terms associated with the coupled physical process. Furthermore, the highly nonlinear and singular nature of the logarithmic error terms makes the convergence analysis even more challenging, since a uniform distance between the numerical solution and the singular limit values of is needed for the associated error estimate. Many highly non-standard estimates, such as a higher order asymptotic expansion of the numerical solution (up to the third order accuracy in time and fourth order in space), combined with a rough error estimate (to establish the maximum norm bound for the phase variable), as well as a refined error estimate, have to be carried out to conclude the desired convergence result. To our knowledge, it will be the first work to establish an optimal rate convergence estimate for the Cahn–Hilliard–Navier–Stokes system with a singular energy potential.

Company Management: The Influence of Organizational Structure and Leadership on Team Performance

This research is driven by a need to gain insight into the key roles that effective leadership plays in achieving optimal performance within teams. In order to fully comprehend the dynamics of team leadership, it is essential to have a robust theoretical and conceptual framework in place. This understanding will help us to identify the factors that influence team performance, and in particular, the role that effective communication, positive feedback, rewards and recognition, and the creation of a supportive work environment plays in motivating teams. In addition, it is vital to consider the key factors that influence the performance of high-functioning teams, which include elements such as team trust, collaboration, effective communication, and leader support. This research employs the methodology of a literature study to ascertain the role of leadership in organizations. In conclusion, team leadership plays an essential role in achieving effective team performance in organizations. By developing a robust theoretical and conceptual framework, leaders can cultivate the practical and strategic insights necessary to lead teams effectively. Effective leaders influence team performance motivation, manage conflict, build cooperation, and create a supportive work environment. The significance of effective team performance is also evidenced by the key factors that influence great team performance. In practice, leaders must be able to apply these insights in a practical manner in order to achieve the desired results.

КОНСЕРВАТИВНЫЕ МЕТОДЫ ЛЕЧЕНИЯ ГРЫЖ МЕЖПОЗВОНКОВЫХ ДИСКОВ

In the modern world, herniated intervertebral discs are one of the most common pathologies, often occurring among the working-age population. Protrusion of the intervertebral disc beyond the cross-section of the vertebra can lead to severe pain (even disability) due to mechanical compression of the nerve root and, with extrusion of the nucleus pulposus, inflammatory reactions. Thus, to date, pain syndrome that has developed as a result of a hernia occurs in 9% of the world's population. Thus, the treatment of intervertebral hernias is one of the pressing problems of the modern world. Radical treatment - surgical, is associated with a number of complications and does not always lead to the desired results. For this reason, surgical treatment should be carried out only if conservative methods are ineffective, among which physiotherapy occupies a special place. The purpose of this work is a literary analysis of physiotherapy methods currently used for the treatment of herniated intervertebral discs and to determine their place in the complex therapy of this pathology. The review examines the nature of intervertebral hernias, some of the physiological reactions they cause, in particular, the mechanisms of pain syndrome formation are indicated. We also described in detail the main methods of physiotherapy currently used for herniated intervertebral discs, such as electrophoresis, balneological procedures, spinal traction; the mechanisms of their influence on the damaged intervertebral disc are indicated, allowing to eliminate or reduce the intensity of the pain syndrome; The need for an integrated approach in the treatment of the pathology under study was determined.

Inversion of the Permeability Coefficient of a High Core Wall Dam Based on a BP Neural Network and the Marine Predator Algorithm

The parameters’ inversion of saturated–unsaturated is important in ensuring the safety of earth dams; many scholars have conducted some research regarding the inversion of hydraulic conductivity based on seepage pressure monitoring data. The van Genuchten model is widely used in saturated–unsaturated seepage analysis, which considers the permeability connected to the water content of the soil and the soil’s shape parameters. A BP neural artificial network is a mature prediction technique based on enough data, and the marine predator algorithm is a new nature-inspired metaheuristic inspired by the movement of animals in the ocean. The BP neural artificial network and marine predator algorithm are applied in the permeability coefficient inversion of a core-rock dam in China; the results show that in the normal operation status, the BP network shows better accuracy, and the average of the absolute error and variance of the absolute error are both minimum values, which are 2.21 m and 1.43 m, respectively. While the water storage speed changes, the marine predator algorithm shows better accuracy; the objective function is calculated to be 0.253. So, the marine predator algorithm is able to accurately reverse the desired results in some situations. According to the actual condition, employing suitable methods for the inverse permeability coefficient of a dam can effectively ensure the safe operation of dams.

Influence of Tool Inclination and Effective Cutting Speed on Roughness Parameters of Machined Shaped Surfaces

Free-form surfaces in the automotive or aviation industry where the future shape of the product will contain complex surfaces raises the question of how to achieve the necessary shape of the required quality in the milling process. One of the methods of their production is the use of 5-axis milling, in which it is necessary to consider not only the input data of the process itself, but also the methodology for evaluating the desired results. Correctly answered questions can thus facilitate the choice of the inclination of the tool when machining parts of the surfaces defined in the experiment. The primary goal of the paper was to monitor the influence of tool inclination on the quality of the machined surface and effective cutting speed by evaluating surface roughness and surface topography. The experiment was designed to show the effect of different tool positions while the feed per tooth fz for the finishing operation remained constant. The best result in terms of surface quality was achieved with a tool inclination of 15° in the cutting process. The most unfavorable result was obtained with a tool axis inclination of zero degrees due to unfavorable cutting conditions.

Intensity-modulated radiotherapy quality assurance by alanine-EPR and gel dosimetry of a simulated prostate treatment with bilateral metallic prostheses

The presence of metallic prostheses in patients undergoing prostate radiotherapy treatment can lead to scattered doses, compromising treatment reproducibility. This study aims to assess doses in the Planning Target Volume (PTV) and surrounding areas using a water phantom containing pelvic bones and bilateral metallic prostheses. Intensity Modulated Radiotherapy (IMRT) with optimization tools avoiding input dose to the prosthesis was employed. Experimental verification utilized a modified Fricke xylenol orange gel dosimeter (FXO-f) in a 63 mm diameter, 100 mm height cylinder (310 ml volume) for PTV dose checks, and alanine dosimeters for assessing doses in the PTV vicinity and near metallic prostheses. Evaluating doses near prostheses is vital as post-radiotherapy prosthesis loosening has been speculated, possibly linked to overexposure. Gamma evaluation with FXO-f dosimeter yielded approved gamma indices in 97.7% of data points versus TPS, indicating good agreement with linear accelerator-reproduced results. Alanine dosimeter results ranged between (1.0 ± 0.3), (1.2 ± 0.3) Gy, (1.4 ± 0.3) Gy, and (2.0 ± 0.3) Gy, which are comparable to TPS-calculated doses within the dosimeter volume. This result indicates that the heterogeneity correction applied by the Analytical Anisotropic Algorithm used for dose calculation and the avoidance tool employed in the treatment planning could addressed the problem. In summary, this study demonstrates that the treatment technique entering fields towards prostheses, with optimization tools to produce the desirable results.

Enhancing vessel arrival time prediction: A fusion-based deep learning approach

The logistic community of shippers has struggled to predict the precise arrival time of the seagoing vessels with reliable certainty. While deep-learning approaches are promising, the existing methods fail to provide desirable results due to a shallow prediction architecture. This research work proposes a method to predict vessel arrival time that could eventually be incorporated into an intelligent decision support system that we call Vessel Arrival Time Prediction (VATP). VATP presents a hybrid architecture of Convolutional Neural Networks (CNNs), Long Short-Term Memory (LSTM), Attention mechanism, Dropout, and Dense layers to take advantage of the coarse-grained local features produced by CNN, the longitudinal nature of AIS (long-time dependencies) via LSTM and paying attention to the influence feature on the arrival time. While many prior approaches have relied solely on AIS data, and some incorporated a combination of AIS and vessel information, our method also integrates diverse data sources, including Automatic Identification System (AIS), Augmented information (Ain), and Maritime Weather Data (MWD). Furthermore, only a few methods have considered weather information, often using minimal weather-related features. In contrast, our approach involves a comprehensive range of weather-related features, and besides these data sources, we extracted specially crafted features.To verify the effectiveness of VATP, we conducted our experiment on large-scale datasets. The VATP model obtained a Root Mean Square Error (RMSE) of 10.63 and a Mean Absolute Percentage Error (MAPE) of 35.11 %. Our results demonstrate that VATP achieves significant performance. Furthermore, these positive results demonstrate that i) the accuracy of the VATP approach can be improved using the AIS, MWD, and Ain information; ii) learning from a unified feature set can result in a significant performance improvement compared to learning from a subset of the features; iii) we also obtained a superior performance in comparison with other well-known methods in the literature and various state-of-the-art baseline methods. Finally, our results illustrate the consistent performance of the VATP across different datasets.

IMPACT OF AI ON BUSINESS MANAGEMENT

Business management is a broad field that includes everything from high-level decision-making and goal-setting to personnel supervision, financial management, and operational optimization to ensure that it runs smoothly and produces the desired results. Businesses in a variety of industries depend on effective company management to succeed. AI has a major impact on almost every field whatever it may be, that means education, marketing, banking etc. With so many benefits, artificial intelligence is a key component of corporate management. Enterprises can reap numerous advantages from machine learning and artificial intelligence technologies that enhance their functioning. Organizations may operate more efficiently, quickly, and productively thanks to AI and machine learning technologies. Along with greater monitoring capabilities, new business model expansion opportunities, better customer service, and a decrease in human error, these technologies also have the ability to produce results that are higher quality and more dependable.

Scanning Electron Microscopy.

Scanning electron microscopy (SEM) remains distinct in its ability to allow topographical visualization of structures. Key elements to consider for successful examination of biological specimens include appropriate preparative and imaging techniques. Chemical processing induces structural artifacts during specimen preparation, and several factors need to be considered when selecting fixation protocols to reduce these effects while retaining structures of interest. Particular care for proper dehydration of specimens is essential to minimize shrinkage and is necessary for placement under the high-vacuum environment required for routine operation of standard SEMs. Choice of substrate for mounting and coating specimens can reduce artifacts known as charging, and a basic understanding of microscope settings can optimize parameters to achieve desired results. This article describes fundamental techniques and tips for routine specimen preparation for a variety of biological specimens, preservation of labile or fragile structures, immune-labeling strategies, and microscope imaging parameters for optimal examination by SEM. © 2024 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Chemical preparative techniques for preservation of biological specimens for examination by SEM Alternate Protocol 1: Practical considerations for the preparation of soft tissues Alternate Protocol 2: Removal of debris from the exoskeleton of invertebrates Alternate Protocol 3: Fixation of colonies grown on agar plates Alternate Protocol 4: Stabilization of polysaccharide structures with alcian blue and lysine Alternate Protocol 5: Preparation of non-adherent particulates in solution for SEM Support Protocol 1: Application of thin layer of adhesive on substrate to improve adherence Support Protocol 2: Poly-L-lysine coating specimen substrates for improved adherence Support Protocol 3: Microwave processing of biological specimens for examination by SEM Basic Protocol 2: Critical point drying of specimens Alternate Protocol 6: Chemical alternative to critical point drying Basic Protocol 3: Sputter coating Alternate Protocol 7: Improved bulk conductivity through "OTOTO" Basic Protocol 4: Immune-labeling strategies Alternate Protocol 8: Immune-labeling internal antigens with small gold probes Alternate protocol 9: Quantum dot or fluoronanogold preparations for correlative techniques Basic Protocol 5: Exposure of internal structures by mechanical fracturing Basic Protocol 6: Exposure of internal structures of tissues by fracturing with liquid nitrogen Basic Protocol 7: Anaglyph production from stereo pairs to produce 3D images.

THERAPEUTIC OPTIONS IN CALCIFIC ROTATOR CUFF TENDINOPATHY OF THE SHOULDER

Calcific tendinopathy in the tendons of the rotator cuff muscles of the shoulder is an increasingly common and disabling pathology. Calcific tendinopathy is a common disease that mainly affects people aged between 40 and 60. Women seem to be more affected than men. It has been suggested that various factors play a role in the condition, such as abnormal thyroid gland activity, metabolic diseases (e.g. gout, diabetes) and genetic predisposition. Various aetiological hypotheses have been put forward: the degenerative and multiphasic theories are the two most widely accepted. Clinically, calcific tendonitis is characterised by severe, disabling pain, often occurring spontaneously, usually in the morning or following exertion disproportionate to subsequent symptoms. There may be concomitant stiffness, giving rise to a clinical picture resembling frozen shoulder or hyperalgesic painful shoulder. Conventional radiography of the shoulder is the most appropriate imaging approach, but perfectly complemented by soft tissue ultrasound. Most acute painful episodes resolve spontaneously symptomatically. Numerous conservative treatments have been reported in the literature with varying levels of evidence of efficacy. In the present study we tried to evaluate which therapeutic option could give superior results both from a functional, lesional architectural and causal point of view in terms of reduction of callus size, but also from an imaging point of view. The use of various therapeutic protocols have shown a significant benefit of the association of ESWT with conventional FKT, and intra-articular infiltration, with a plus for the association of Corticosteroids and Sodium Hyaluronate regarding the speed of achieving the desired results. Similar results were obtained with the intra-articular shoulder PRP technique, but with slower achievement of the desired results. Arthroscopic surgery is the orthopaedic specialist's last option. Keywords: Calcific tendinopathy, rotator cuff muscles, shoulder, intra-articular infiltration.

Induction of diploid gynogenesis in Micropterus salmoides using irradiated heterogeneous sperm from Siniperca chuatsi

The artificial induction of gynogenesis in fish breeding can be used to produce monosex populations. Micropterus salmoides (largemouth bass) is an important freshwater aquaculture fish, and the females grow faster than the males. In this study, we aimed to determine the best way to artificially induce largemouth bass spawning and identify suitable heterologous sperm donors to induce gynogenetic largemouth bass by suppressing extrusion of the second polar body in fertilized eggs. With respect to the artificial induction of spawning in LB, four groups were tested for hormone types. The results showed that a single intramuscular injection of the hormone combination HCG (2000 IU/kg) + LHRH-A2 (20 μg/kg) + DOM (5 mg/kg) into female largemouth bass could yield desirable spawning results, and the mean number of eggs per female in kg was 28,780 ± 4574. With respect to suitable sperm donors, largemouth bass eggs were fertilized with sperm from five fish species, and it was found that mandarin fish (Siniperca Chuatsi) sperm can activate the development of largemouth bass eggs, but most of the embryos died during development, which indicated that mandarin fish are the potential of suitable heterologous sperm donors for gynogenetic experiments with largemouth bass. The suitable optimal induction conditions were detected for chromosome doubling. The results indicated that the most effective method for promoting gynogenesis in largemouth bass was to expose inseminated eggs to a temperature of 3 °C for 15 min, beginning 2 min after fertilization. In addition, the DNA content, karyotype and morphological characteristics of the gynogenetic offspring were consistent with those of the largemouth bass. Examination of sex-specific markers and artificial propagation of the gynogenetic largemouth bass revealed that all the tested fishes were female, indicating female homogamety (XX) in the largemouth bass. In summary, in this study, we established an improved artificial spawning technique for largemouth bass and successfully induced diploid gynogenetic largemouth bass using irradiated heterogeneous sperm from mandarin fish. Our study lays a foundation for the mono-sex breeding of largemouth bass.

Rwanda-Conflict, Violence, and Reconstruction

When it comes to Rwanda, most people first think of the tragic movie The Rwanda Hotel. That film recreates the bloody 1994 massacre in Rwanda, causing irreparable harm to every Rwandan people. Rwanda's history is indeed full of hatred and misery. After the massacre, the Rwandan government led the people to take national reconstruction measures for the country and achieved the desired results. Based on adjusting their own culture, the Rwandans also explored a development path that suits their national conditions and has African characteristics. After the completion of the reconstruction, Rwanda largely resumed its economic development and made all-around progress, even known as the Singapore of Africa. Rwanda's reconstruction policy is generally improving, but there are still some shortcomings that need to be adjusted and improved. Driven by those reconstruction measures, Rwanda has achieved remarkable results and is worth learning from other countries.

Two-dimensional Ti3C2Tx anchored on three-dimensional SiC honeycomb framework for efficient and cyclic photocatalytic degradation of organic pollutants

The excellent recyclability of SiC foam renders it an ideal catalyst in the field of photocatalytic degradation, however to further improve its photocatalytic efficiency remains a major challenge in current research. In this regard, a honeycomb-like porous SiC foam was successfully constructed through freeze-drying and polymer-to-ceramic derivation method, with two-dimensional Ti3C2Tx nanosheets anchored on its three-dimensional framework. Their photocatalytic performances were evaluated by the degradation of methylene blue (MB) under visible-light irradiation. All Ti3C2Tx/SiC hybrid foams show superior photocatalytic degradation capability compared with SiC foam, with a highest removal rate (adsorption and degradation) reaching 94.4% for TSF-4, denoting an increasement of 50.4%. Even after five cycles, the removal rate remained at 91.4% with only a slightly loss of 3%, suggesting its excellent recycling performance. These desirable results stem from the unique structural design, in which the porous structure facilitates the contact between catalyst and pollutant, while the Ti3C2Tx/SiC heterojunction promotes effective separation of photogenerated carriers. This work paves the way for the development of lightweight, efficient and easily recyclable photocatalyst for wastewater purification.

Image Caption Generator using Deep Learning

Image Caption Generation has always been a study of great interest to the researchers in the Artificial Intelligence department. Being able to program a machine to accurately describe an image or an environment like an average human has major applications in the field of robotic vision, business and many more. Automatic caption generation with attention mechanisms aims at generating more descriptive captions containing coarse to fine semantic contents in the image. This has been a challenging task in the field of artificial intelligence. In this paper, we present different image caption generating models based on deep neural networks, focusing on the various CNN techniques and analyzing their influence on the sentence generation. We have also generated captions for sample images and compared the different feature extraction and encoder models to analyse which model gives better accuracy and generates the desired results

Development of hBN/natural fibres reinforced polymer composites using grey relation grade analysis for thermal and electrical applications

The objective of this work is to enhance the thermal conductivity and electrical properties of polymer hybrid composites through a systematic novel grey relation grade analysis (GRGA) optimization approach. This involves reinforcing the hybrid composites with hexagonal boron nitride (hBN) and various kinds of natural fibers or fillers. The development of a unique technology to produce multiphase composites using 2% of natural fibers or fillers such as coir fiber, rice husk filler, wood filler (WF), banana fiber (BF) and sugarcane fiber along with hBN (1, 3, 5 wt.%) particulates as reinforcements in epoxy matrix. The Taguchi L15 matrix array is utilized to fabricate interlaced composite samples via hand layup molding. Ultrasonic waves are used to ensure the uniform distribution of hBN filler into the matrix. Analysis of variance and GRGA reveal the significant results. It shows that the multiphase hybrid composites exhibit good thermal conductivity when higher content of hBN (5 wt.%) particulate for all the micro particulate polymer (MPP) composites. Multi-response optimization shows that the micro BF (2 wt.%) interlaces with hBN (5 wt.%) composite exhibits the higher thermal conductivity and electrical resistance compared to all other natural fiber interlaced composites. The aforementioned MPP composite has thermal conductivity of 1.03 W (m·K)−1 and electrical resistance of 279.88 Giga Ohms. Besides, the WF interlaced hBN (5 wt.%) composite shows the minimum dielectric constant compared to all other natural fiber composites. This desirable result is caused by the proper dispersion of hBN with the matrix which encourages interlocking with the fiber and the matrix. Maximum electrical resistance is observed for composite containing 5 wt.% of h-BN and 2 wt.% of BF. The developed MPP composite could be used in heat shields, electrical insulation components, and interior automotive components like dashboards, luggage compartments and interior walls.

Towards geodesic ridge curve for region-wise linear representation of geodesic distance field

This paper addresses the challenge of representing geodesic distance fields on triangular meshes in a piecewise linear manner. Unlike general scalar fields, which often assume piecewise linear changes within each triangle, geodesic distance fields pose a unique difficulty due to their non-differentiability at ridge points, where multiple shortest paths may exist. An interesting observation is that the geodesic distance field exhibits an approximately linear change if each triangle is further decomposed into sub-regions by the ridge curve. However, computing the geodesic ridge curve is notoriously difficult. Even when using exact algorithms to infer the ridge curve, desirable results may not be achieved, akin to the well-known medial-axis problem. In this paper, we propose a two-stage algorithm. In the first stage, we employ Dijkstra's algorithm to cut the surface open along the dual structure of the shortest path tree. This operation allows us to extend the surface outward (resembling a double cover but with distinctions), enabling the discovery of longer geodesic paths in the extended surface. In the second stage, any mature geodesic solver, whether exact or approximate, can be employed to predict the real ridge curve. Assuming the fast marching method is used as the solver, despite its limitation of having a single marching direction in a triangle, our extended surface contains multiple copies of each triangle, allowing various geodesic paths to enter the triangle and facilitating ridge curve computation. We further introduce a simple yet effective filtering mechanism to rigorously ensure the connectivity of the output ridge curve. Due to its merits, including robustness and compatibility with any geodesic solver, our algorithm holds great potential for a wide range of applications. We demonstrate its utility in accurate geodesic distance querying and high-fidelity visualization of geodesic iso-lines.

Love burnout: young women, mobile phones, and delayed marriage in Yaoundé, Cameroon

AbstractThis article examines how work towards the promise of love marriage comes to be exhausted. It focuses on young urban women living in Yaoundé, Cameroon, trying to ‘catch’ a husband using digital technologies in which photographs figure prominently. Focusing on the visual production of dating profiles, I show how mobile phones place young women at the centre of their own husband‐catching pursuits. Through digital actions, these young women produce the promise of love marriage, but at the same time their actions require increased volumes of emotional work. As phones constantly compel young women to intensify their husband‐catching efforts and amplify the promise of love marriage, they rarely bring the desired results. Thus, young women, burdened by the emotional work necessary to sustain this promise, experience a form of love burnout, suspend their actions, and delay marriage. In highlighting the emotional laboriousness of intimate relations in technologically mediated worlds, this article draws out the limitations of the way in which the promise of love marriage is circulated and points to how neoliberal economies of affect may be temporarily suspended.

Ecological dyeing and UV-protective functionalization of cotton/lyocell blend fabrics designed for high comfort summer clothing

Wearing clothes that absorb or block harmful UV radiation is one of the most effective forms of protection against sun damage and skin cancer. In the current study, sustainable processes which will provide high clothing comfort and a sufficient level of UV protection for fabrics used in production of lightweight sun-protective summer clothing were proposed. In accordance with the scope of the study, structural properties, low-stress mechanical properties, surface characteristics, permeability, and UV-protection properties of three woven fabrics produced with different weft settings and lyocell ratios were determined. The fabric type which had the most desirable results was selected for dyeing experiments. Avocado (Persea americana) seed was used as an eco-friendly source for dyeing and UV-protective functionalization of cotton/lyocell blend fabric. To obtain different hues, the fabrics were mordanted according to two different recipes using magnesium sulphate and ferrous sulphate and dyed with the natural colorant extracted from avocado seeds. Comfort, color, fastness, and UV-protective properties of dyed samples were evaluated by laboratory tests. Results indicated that it is possible to achieve an excellent level of UV protection (UPF 50+) by dyeing cotton/lyocell blend fabrics with avocado seed extract and produce summer clothing with improved comfort and UV-protective properties, without using any toxic materials.