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The objective of this work is studying the use of chemicals to enhance primary treatment in municipal wastewater treatment plants, thereby reducing the cost of the secondary treatment stage. Jar tests using chemicals, polymers and sea water have been conducted to determine the best performing chemicals, alone and in combinations. The process performance parameters studied were pH, type and dosage of coagulant, mixing intensity, detention time, settling time and addition of coagulant aid. The efficiency of the process has been measured as percentage removals in COD, TSS, turbidity, settleable matter and removals of heavy metals. The results proved the improvement of removal efficiencies.

As host to over one million Syrian refugees, Lebanon continues to experience challenges addressing the needs of refugee families. This research examined the experiences of Syrian families with the refugee support system in Lebanon. The purpose of this study was to better understand the strengths and gaps in existing mechanisms of support for these Syrian families, including informal support from family, neighbors and community and more formalized support provided through entities such as nongovernmental organizations and United Nations agencies.

Data were collected from 46 families displaced by the war and living in Lebanon (N = 351 individuals within 46 families). Collaborative family interviews were conducted with parents, children and often extended family.

The data identified both strengths and gaps in the refugee support system in Lebanon. Gaps in the refugee support system included inadequate housing, a lack of financial and economic support, challenges with a lack of psychosocial support for pregnant women and support for disabled youth. Despite these challenges, families and community workers reported informal community support as a strong mediator of the challenges in Lebanon. Furthermore, the data find that organizations working with Syrian families are utilizing informal community support through capacity building, to create more effective and sustainable support services.

This study provides an overview of strengths and gaps in supports identified by refugees themselves. The research will inform the development and improvement of better support systems in Lebanon and in other refugee–hosting contexts.

The purpose of this study is to develop resin composite materials composed of polycaprolactone (PCL) acrylates and hydroxyapatite (HA) nanoparticles for ultraviolet digital light projection (DLP) three-dimensional (3D) printing technique.

Two PCL-based triacrylates, namely, glycerol-3 caprolactone-triacrylate (Gly-3CL-TA) and glycerol-6 caprolactone-triacrylate (Gly-6CL-TA) were synthesized from ring-opening polymerization of ε-caprolacton monomer in the presence of glycerol and then acrylation was performed using acryloyl chloride. 3D printing resins made of Gly-3CL-TA or Gly-6CL-TA, 5% HA and 3% of photoinitiator 2,4,6-Trimethylbenzoyl-diphenyl-phosphineoxide were then formulated. The surface topography, surface element composition, flexural strength, flexural modulus, cytotoxicity and degradation of the PCL-based scaffolds were then characterized.

Resin composite composed of Gly-3CL-TA or Gly-6CL-TA and 5% (w/w) of HA can be printed by 405 nm DLP 3D printers. The former has lower viscosity and thus can form a more uniform layer-by-layer structure, while the latter exhibited a higher flexural strength and modulus after being printed. Both composite materials are non-cytotoxic and degradable.

This study provides a direction of the formulation of environment-friendly resin composite for DLP 3D printing. Both resin composites have huge potential in tissue engineering applications.

Milk is often referred to as the ultimate food because it meets the nutritional needs of infants, children and adults alike. It is a rich source of protein, fat, sweetness, vitamins and minerals. Because of its widespread usage as a healthy dairy product, the issue of milk adulteration is of global significance. The increasing frequency of fraudulent methods in the dairy business raises concerns about its purity and quality.

A study was conducted and reviewed that looked at several approaches for detecting milk adulteration during the past 15 years. This study examines the current state of research and analyzes recent advances in development.

There are ways and technology available that can effectively put an end to the abhorrent practice of milk adulteration.

This research takes a unique approach, focusing on the application of milk adulteration. It provides an overview of milk adulteration detection and investigates the effectiveness of biosensors in identifying common milk adulterants.

The purpose of this paper is to present a novel photomask auto‐correction method for the area‐forming rapid prototyping (RP) system.

A digital light processing (DLP) projector was used in this research as a light source to generate the photomask image. A set of optical lenses were mounted in front of the DLP to rescale the photomask image. The rescaled photomask image was collected into a computer via a camera. By using the technique of image processing, the actual size of the photomask was then calculated. The designed size of the photomask image was eventually achieved by adjusting the relative locations of the lenses.

It was found that this proposed photomask auto‐correction method can produce a more accurate dimension of the photomask image and perform with higher efficiency than the manual calibration processes.

The paper is believed to be the first work to use the image‐processing technique to calibrate the photomask of an area‐forming RP system, as well as to employ a method of adjusting the relative position between the lenses to rescale the photomask image size.

The aim of this study is to optimize the process parameters of area-forming rapid prototyping system to improve the model dimensional repeatability and to minimize the process time as well.

Model dimensional repeatability is based on the dimensional standard deviation of the test sample. The significant factors that affect the model dimensional repeatability and process time are established by the fractional factorial design. Response surface methodology, based on the central composite design, is applied to evaluate the regression models of the response variables including prototype’s dimensional repeatability and processing time. Finally, a desirability function for each individual response variables is constructed to obtain the optimal process parameters.

The significant factors that have an impact on the main effects of response variables model dimensional repeatability and process time found by the fractional factorial design are curing time, light flux and platform moving velocity.

All previous studies were concerned with product accuracy in area-forming rapid prototyping system. In this work, we focus on optimization of model dimensional repeatability.

Solid freeform fabrication is particularly suitable for fabricating customized parts, but it has not been used for fabricating deployable structures that can be stored in a compact configuration and deployed quickly and easily in the field. The purpose of this paper is to present a methodology for deploying flexible, freeform structure with lattice skins as the deploying mechanism.

A ground structure‐based topology optimization procedure is utilized, with a penalization scheme that encourages convergence to sets of thick lattice elements that are manufacturable and extremely thin lattice elements that are removed from the final structure.

A deployable wing is designed for a miniature unmanned aerial vehicle. A physical prototype of the optimal configuration is fabricated with selective laser sintering and compared with the virtual prototype. The proposed methodology results in a 78 percent improvement in deviations from the intended surface profile of the deployed part.

The results presented in the paper provide proof‐of‐concept for the use of lattice skins as a deployment mechanism. A topology optimization framework is also provided for designing these lattice skins. Potential applications include portable, camouflaged shelters and deployable aerial vehicles.

We introduce decision support tools aimed at optimizing perishable food supply chain management, effectively balancing conflicting objectives such as the exporter’s product collection cost and the importer’s profit. This involves considering factors like perishability, selling price, discount rate, and order quantity to achieve optimal outcomes.

This study considered a three-echelon supply chain comprising farmers, a single exporter, and a single importer providing a single, random-lifetime, perishable product under deterministic customer demand. The proposed mathematical model derived the optimal order quantity, selling price, and discount rate for the entire supply chain. This integrated optimization model treats both demand and supply sides as a multi-objective problem, employing a nonlinear program and a two-stage capacitated vehicle routing problem formulation. Numerical examples and a case study focusing on Thailand durian supply chain were conducted to illustrate the approach of the proposed model.

Taking into account both the importer’s profit and the exporter’s product collection cost, the proposed integrated supply chain model and tools maximize profitability, minimizes waste, and meets demand by optimizing perishable product collection costs and proposing a discount system for selling prices.

Limited to a single perishable product in a three-echelon international food supply chain. Future research can explore different products and supply chain contexts.

The tools enhance decision-making for supply chain managers, improving efficiency, reducing costs, and enhancing customer satisfaction in the perishable food industry.

The proposed model aids in local workforce management by forecasting required manpower for upcoming seasons. By factoring in product quality and pricing, it ensures customers receive fresh products at fair prices. Furthermore, the near-zero waste concept enhances storage conditions at importers' facilities, contributing to improved environmental hygiene.

The integrated model and decision support tools offer a novel approach to address complexities and conflicting objectives in perishable food supply chains, providing practical insights for researchers and practitioners.

Frontier environments – such as battlefields, hostile territories, remote locations, or outer space – drive the need for lightweight, deployable structures that can be stored in a compact configuration and deployed quickly and easily in the field. This paper seeks to introduce the concept of lattice skins is introduced to enable the design, solid freeform fabrication (SFF), and deployment of customizable structures with nearly arbitrary surface profile and lightweight multi‐functionality.

Using Duraform^® FLEX material in a selective laser sintering machine, large deployable structures are fabricated in a nominal build chamber by decomposing them into smaller parts. Before fabrication, lattice sub‐skins are added strategically beneath the surface of the part. The lattices provide elastic energy for folding and deploying the structure or constrain expansion upon application of internal air pressure. Nearly, arbitrary surface profiles are achievable and internal space is preserved for subsequent usage.

A set of virtual and physical prototypes are presented, along with the computational modeling approach used to design them. The prototypes provide proof of concept for lattice skins as a deployment mechanism in SFF and demonstrate the effect of lattice structures on deployed shape.

The research findings demonstrate not only the feasibility of a new deployment mechanism‐based on lattice skins – for deploying freeform structures, but also the potential utility of SFF techniques for fabricating customized deployable structures.

A new lattice skin mechanism is introduced for deploying structures with nearly arbitrary surface profiles and open, usable, internal space. Virtual and physical prototypes are introduced for proof of concept, along with an optimization approach for automated design of these structures.

Women pursuing male-dominated careers face well-documented barriers to career success (e.g., stereotypes, sexual harassment, limited access to professional networks, and mentoring), which have the potential to be exacerbated or diminished by the increasing prevalence of work from home (WFH). In this chapter, the authors first review key career obstacles for women in male-dominated fields and analyse the impact of WFH on these barriers and, second, provide actionable strategies for organisations to implement WFH in a way that promotes rather than hampers the success of women in these fields. Both career obstacles and WFH remedies are considered through an overarching framework focussed on the significance of work–family boundary management, inclusion, and career advancement. Drawing on the extant research, the authors provide evidence-based, actionable guidance to help organisations and supervisors leverage WFH to support the career success of women in male-dominated careers.