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The purpose of the present study is to investigate the effects of strain-induced martensite (SIM) and its reversal on metastable austenitic stainless steel (MASSs) through the analysis of metallurgical and sensitisation behaviour.

In the present investigation, the samples of Cr-Mn ASS (also known as MASSs) including 15%, 30% and 50% cold worked, solution annealed samples with and without thermal ageing (at 700°C for 3 h) were analysed with the help of X-ray diffraction analysis, microstructure examination and electrochemical behaviour. The scanning electron microscope (SEMJOEL 6380 A) was used to examine the microstructure of the sample, and the double-loop electrochemical potentiokinetic reactivation test was used to determine the degree of sensitisation (DOS) in the samples. The cold worked solution annealed samples without thermal ageing are named as CR15, CR30 and CR50, respectively, and the samples with thermal ageing are named as CR15_TA, CR30_TA and CR50_TA, respectively.

In CR15, CR30 and CR50 samples, the DOS increased with increase in the extent of cold working, which was attributable to passivation deterioration. Because of the high degree of passivation at the grain boundaries, the DOS of CR15_TA and CR30_TA were practically identical. The DOS in the CR50_TA sample, on the other hand, was lowered due to SIM recovery in the austenite.

The present study sheds light on how to choose the right cold working percentage to avoid sensitisation in MASSs during the fabrication of metal forming components.

The purpose of this study is to outline the specific details and lessons learned during a cold case collaborative effort, which granted graduate students and a professor from the University of South Florida the opportunity to assist Pasco Sheriff’s Office in the investigation of a cold case homicide.

The collaboration between law enforcement and academics is a new and emerging strategy to investigate cold cases and identify the elusive offenders who committed these crimes. Such collaboration aids law enforcement by obtaining a force multiplier for investigative resources, accessing cutting-edge evidence-based research and cultivating innovative approaches to their work. For academics, such collaboration allows the unique opportunity to engage in translational criminology, which is an important and increasingly encouraged aspect of the field.

In this paper, the authors provide an overview of the process used to study this cold case as part of an experiential academic course, provide evidence-based research findings relevant to cold case investigations and outline the steps for others to replicate the efforts.

The authors describe in detail the process used to “work” the cold case, academic research that the authors found useful in understanding and investigating cold cases, important lessons learned and advice for future academics and practitioners who undertake an incredible collaborative effort such as this.

As a result of advances in DNA and other forensic technologies, police agencies are showing increased interest in cold-case investigations, with larger departments dedicating staff to conducting these investigations or forming cold-case squads. The purpose of this paper is to provide information on how police agencies organize and conduct cold-case investigations.

To assess the current practices used in cold-case investigations, an exploratory survey was sent to a stratified random sample of police agencies across the US survey findings are based on 1,051 returns.

Results include the following. Most agencies do little cold-case work, with only 20 percent having a protocol for initiating cold-case investigations, 10 percent having dedicated cold-case investigators, and 7 percent having a formal cold-case unit. Cold-case funding is tenuous: 20 percent of cold-case work is funded through line items in the budget, with most funded by grants or supplemental funds. Success rates for cold-case investigations are low: about one in five cases are cleared. Agency factors associated with higher clearance rates included level of funding and access to investigative databases.

As new forensic tools are developed, cold-case investigations will become an increasingly prominent activity of criminal investigation units. The survey reported on in this paper gives the first glimpse of how agencies are handling these cases.

To the knowledge, there are no other empirical studies on how agencies structure and conduct cold-case investigations.

Since the handling of environmentally sensitive products requires close monitoring under prescribed conditions throughout the supply chain, it is essential to manage specific supply chain risks, i.e. maintaining good environmental conditions, and ensuring occupational safety in the cold environment. The purpose of this paper is to propose an Internet of Things (IoT)-based risk monitoring system (IoTRMS) for controlling product quality and occupational safety risks in cold chains. Real-time product monitoring and risk assessment in personal occupational safety can be then effectively established throughout the entire cold chain.

In the design of IoTRMS, there are three major components for risk monitoring in cold chains, namely: wireless sensor network; cloud database services; and fuzzy logic approach. The wireless sensor network is deployed to collect ambient environmental conditions automatically, and the collected information is then managed and applied to a product quality degradation model in the cloud database. The fuzzy logic approach is applied in evaluating the cold-associated occupational safety risk of the different cold chain parties considering specific personal health status. To examine the performance of the proposed system, a cold chain service provider is selected for conducting a comparative analysis before and after applying the IoTRMS.

The real-time environmental monitoring ensures that the products handled within the desired conditions, namely temperature, humidity and lighting intensity so that any violation of the handling requirements is visible among all cold chain parties. In addition, for cold warehouses and rooms in different cold chain facilities, the personal occupational safety risk assessment is established by considering the surrounding environment and the operators’ personal health status. The frequency of occupational safety risks occurring, including cold-related accidents and injuries, can be greatly reduced. In addition, worker satisfaction and operational efficiency are improved. Therefore, it provides a solid foundation for assessing and identifying product quality and occupational safety risks in cold chain activities.

The cold chain is developed for managing environmentally sensitive products in the right conditions. Most studies found that the risks in cold chain are related to the fluctuation of environmental conditions, resulting in poor product quality and negative influences on consumer health. In addition, there is a lack of occupational safety risk consideration for those who work in cold environments. Therefore, this paper proposes IoTRMS to contribute the area of risk monitoring by means of the IoT application and artificial intelligence techniques. The risk assessment and identification can be effectively established, resulting in secure product quality and appropriate occupational safety management.

This paper aims to improve operational efficiency and minimize accident frequency in cold storage facilities through adopting an effective occupational safety and health program. The hidden knowledge can be extracted from the warehousing operations to create the comfortable and safe workplace environment.

A fuzzy association rule-based knowledge management system is developed by integrating fuzzy association rule mining (FARM) and rule-based expert system (RES). FARM is used to extract hidden knowledge from real operations to establish the relationship between safety measurement, personal constitution and key performance index measurement. The extracted knowledge is then stored and adopted in the RES to establish an effective occupational and safety program. Afterwards, a case study is conducted to validate the performance of the proposed system.

The results indicate that the aforementioned relationship can be built in the form of IF-THEN rules. An appropriate safety and health program can be developed and applied to all workers, so that they can follow instructions to prevent cold induced injuries and also improve the productivity.

Because of the increasing public consciousness of occupational safety and health, it is important for the workers in cold storage facilities where the ambient temperature is at/below 10°C. The proposed system can address the social problem and promote the importance of occupational safety and health in the society.

This study contributes to the knowledge management system for improving the occupational safety and operational efficiency in the cold storage facilities.

The purpose of this study is to investigate the effect of prior cold work after annealing and thermal ageing on intergranular corrosion or sensitization of Cr-Mn austenitic stainless steel (ASS) is necessary. Such a study is particularly important because ASS are mostly used and welded in mill-annealed condition, which is equivalent to fully annealed material with some cold worked (CW).

The effect of 15% CW of 202 ASS were investigated using microstructural (optical microscope), mechanical (grain size and hardness) and electrochemical methods (double loop electrochemical reactivation [DLEPR]) followed by thermal ageing (800°C, 900°C and 1000°C).

X-ray diffraction analysis shows the presence of martensite in CW samples. The increase in martensite formation (800°C and 900°C) can be observed with the variation of thermal ageing (TA) duration (1, 2 and 3 h). However, there was decreased in the formation of martensite at the temperature of 1000°C because of martensitic reversal. The DLEPR test result shows higher degree of sensitization (DOS) for 800°C and 900°C but for 1000°C, there was re-homogenization of samples which leads to lower DOS (thermal ageing for 1, 2 and 3 h).

For 300 series steel, there are various literature available for the effect of cold work on mechanical properties and DOS. However, no one has investigated the effect of cold work and thermal ageing on the sensitization of 202 Cr-Mn ASS.

The purpose of this paper is to investigate tin pest formation in lead‐free alloys.

Samples of Sn99.5Ag3.0Cu0.5, Sn99Cu1 and Sn98Cu2 alloys were prepared in four different forms. The first group was prepared using traditional PCB technology and a hand soldering method. The next group of samples was composed of as‐received ingots of these alloys. To check the impact of mechanical treatment on the transformation process, additional cold‐worked and cold‐rolled samples were prepared (30 kN). All samples were placed initially either at −18°C or at −65°C for low temperature storage testing. Visual observations, scanning electron microscopy observations and X‐ray diffraction analysis were performed to identify the transformation process. Additional samples were prepared using a force of 75 kN and placed in a chamber at a temperature of −30°C for long‐term testing.

The detectable symptoms of tin pest in samples subjected to mechanical processing with 1 and 2 wt.% of Cu addition stored at −18°C were observed at the edges of the samples after 17 months of storage. Further aging at −18°C showed the progress of α/β transformation with time under low‐temperature stress, but only in these specimens. With the application of greater force to the pressing process (75 kN instead of 30 kN) and at a temperature of storage close to the maximal transformation rate (−30°C), there was a significant acceleration of the α/β transformation, and this dependence can be used in predicting the risk of tin pest occurrence in various lead‐free alloys.

The paper shows that the degree of mechanical processing had a great influence on the α/β transformation rate. Based on these observations, it is proposed that such mechanically processed samples can be used for accelerated testing of tin‐rich lead‐free alloys at low temperatures. Such tests would be appropriate for a practical estimation of the tin pest risk when the design life of some electronic equipment ranges from 15 to 25 years.

The purpose of this paper is to outline a variety of related methods for helping with criminal (cold) case investigations. Despite the best efforts of police investigations, many cases around the world run out of leads and go cold. While many police departments around the world have developed specialist groups and task forces, academics have also been developing new methods that can assist with investigations.

Cold cases, by their very nature, typically comprise incomplete data sets that many traditional statistical methods are not suited to. Groups of researchers have therefore developed temporal, dynamic analysis methods to offer new insights into criminal investigations. These methods are combined into a timeline toolkit and are outlined in the current paper.

Methods from the timeline toolkit have already been successfully applied to many cold cases, turning them back into current cases. In this paper, two real-world cold cases are analysed with methods from the timeline toolkit to provide examples of how these methods can be applied in further cold cases.

Methods from the timeline toolkit provide a novel approach to investigating current and cold cases. This review provides academics and practitioners with a guide to begin using and developing these methods and forming successful collaborations with police departments and cold case task forces. The methods are also suitable for wider groups and to use in their investigations.

The purpose of this paper is to study the kinetics of static recovery in cold-rolled aluminum alloy under different heating rates.

Deformation modeling was first performed to assess the distributions of plastic strain and stress within the deformed alloy. In the next stage, thermal analysis and the rate equation of static recovery were employed to determine the progress of static recovery under non-isothermal conditions. Accordingly, a thermal finite element analysis and the Runge-Kutta method were utilized to handle the transient heat conduction and the progress of static recovery. Finally, low temperature annealing heat treatments were conducted to verify the model predictions. Accordingly, the tensile tests were conducted to measure the yield stresses of cold-rolled plates subjected to the subsequent annealing treatment at different temperatures and durations.

The results indicate that the employed algorithm can be used as an appropriate predictive tool for designing a low temperature heat treatment schedule to achieve the desired yield stress.

The kinetics of non-isothermal recovery and resulting yield stress are well predicted under practical annealing conditions.

Microstructure-sensitive design (MSD), for optimal performance of engineering components that are sensitive to material anisotropy, has largely been confined to the realm of theory. The purpose of this paper is to insert the MSD framework into a finite element environment in order to arrive at a practical tool for improved selection and design of materials for critical engineering situations.

This study applies the recently developed Hybrid Bishop-Hill (HBH) model to map the yield surface of anisotropic oxygen free electronic copper. Combining this information with the detailed local stresses determined via finite element analysis (FEA), a “configurational yield stress” is determined for the entire component. By varying the material choice/processing conditions and selecting the directionality of anisotropy, an optimal configuration is found.

The paper provides a new FEA-based framework for MSD for yield-limited situations. The approach identified optimal directionality and processing configurations for three engineering situations that are particularly sensitive to material anisotropy.

The microstructure design space for this study is limited to a selection of eight copper materials produced by a range of processing methods, but is generalizable to many materials that exhibit anisotropic behavior.

The introduction of MSD methodology into a finite element environment is a first step toward a comprehensive designer toolkit for exploiting the anisotropy of general materials (such as metals) in a way that is routinely undertaken in the world of fiber-based composite materials. While the gains are not as sizeable (due to the less-extreme anisotropy), in many applications they may be extremely important.