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Applications of Raman spectroscopy in bio-sensing and bio-detection were previously limited due to its low sensitivity resulting from weak Raman scattering. Over time, improvements in instrumentation and the discovery of surface-enhanced Raman scattering (SERS) have increased sensitivity and specificity for target analytes, making Raman spectroscopy a technique of choice for many applications, ranging from biomedical to environmental sensing. However, despite significant progress in the field, novel SERS substrates are still being synthesized and tested by researchers to achieve lower detection limits and increase the reproducibility of this technique. Accordingly, substrate materials have developed from traditional plasmonic materials, which provide primarily electromagnetic enhancements, to semiconductor materials that primarily rely on the chemical enhancement mechanism. A diverse body of research has equally explored combining these materials in a hybrid manner with variable results. Notable semiconductor materials include metal oxides ZnO and TiO2, which exhibit high flexibility and integration into SERS sensing designs to potentially enhance sensitivity and modify biocompatibility. In light of these recent developments, this review summarizes recent approaches to synthesize ZnO and TiO2SERS nanostructures and examines recent biological applications of these substrates. Over 60 papers were consulted to develop an overview of current synthesis approaches to integrating ZnO and TiO2into SERS substrates. A summary of various bio-detection applications and potential advancements in the field are presented.

Background: NR2F1mutations are associated with Bosch-Boonstra-Schaaf optic atrophy syndrome (BBSOAS). Although ~ 46.7% of BBSOAS patients present with epilepsy, which is always drug-resistant and associated with higher rates of behavioral and cognitive problems, the treatment and outcomes of NR2F1-related epilepsy have rarely been described. Here, we present new cases of BBSOAS-related epilepsy and summarize all previously reported cases to explore the effective treatment for this type of epilepsy. Methods: We identified six new Chinese cases of BBSOAS with epilepsy. Five different de novo heterozygous NR2F1mutations were identified in these cases, including two novel mutations c.365G > T, p.Cys122Phe and c.449G > T, p.Gly150Val. By combining the six cases and 14 previously reported cases, we analyzed the characteristics and treatment outcomes of NR2F1-related epilepsy. Results: Twelve of the 20 patients (60%) had infantile epileptic spasms, while the other patients had generalized tonic/tonic-clonic, focal, myoclonic, absence, or unclassified seizures. Several anti-seizure medications, steroids, and a ketogenic diet were administered in these cases. However, seizures were controlled in only 50% of previously reported cases, while all of the six new cases became seizure-free after perampanel as an add-on treatment. The average time from the addition of perampanel to seizure control was 7.33 ± 4.59 months (range, 1–12 months). The median time to seizure freedom was 14 months (1–32 months, > 19 months in 3 cases). The average dosage of perampanel needed for epilepsy control was 0.22 ± 0.17 mg/kg per day. Conclusions: In this paper, we comprehensively summarized the clinical characteristics, treatments and outcomes of NR2F1-related epilepsy for the first time. Perampanel exhibits dramatic efficacy for NR2F1-related epilepsy. This will help optimize the treatment of this type of epilepsy and provide clues for its pathogenic mechanisms. The two novel mutations expand the genotype spectrum of this disease.

Background: Nicotine replacement therapy (NRT) and short messaging service (SMS)-based tobacco cessation interventions have demonstrated effectiveness in reducing tobacco use in many populations, but evidence is needed on which tailored treatments are most efficacious in meeting the complex medical and psychosocial factors confronting people living with HIV (PLWH) in sub-Saharan Africa (SSA). This paper describes the protocol of a study to test the efficacy of both NRT and a tailored SMS-based tobacco use cessation intervention among PLWH in Uganda and Zambia. Methods: In a randomized controlled trial, 800 adult PLWH who use tobacco will be recruited by health care professionals at HIV treatment centers where they are receiving care. Participants will be randomized to one of the four study arms: (1) standard of care [SOC; brief clinician advice to quit combined with HIV education and information aimed at encouraging HIV treatment adherence (with no mention of tobacco) delivered via text messages]; (2) SOC + 12 weeks of NRT; (3) SOC + 6 weeks of SMS text messages to support quitting tobacco use (SMS); or (4) SOC + NRT + SMS. Participants will receive a cell phone and solar panel with power bank for charging the phone. The main outcome is cessation of tobacco use by study participants verified by urinary cotinine (< 15 ng/mL) at 6 months post-enrollment. As a secondary tobacco use outcome, we will measure 7-day point-prevalence abstinence (7 consecutive days of no tobacco use) measured by self-report and biochemically-verified at 4 weeks, 8 weeks, and 3 months post enrollment. Discussion: Our study will provide insight into the efficacy, feasibility and applicability of delivering tobacco cessation interventions through health care professionals combined with tailored tobacco cessation SMS text messaging in two countries with different tobacco use patterns, policy environments, and health care resources and provide needed information to providers and policymakers looking for cost-effective tobacco cessation interventions. The previously tested SMS-platform to be used in our study is uniquely positioned to be scaled in low- and middle-income countries worldwide, in which case evidence of even modest success in reducing the prevalence of tobacco consumption among PLWH could confer enormous health and economic benefits.

Elderly individuals commonly experience the risk of dysphagia or difficulties in eating and swallowing food safely. Three-dimensional (3D) food printing is a promising technique widely used in customized food development. This paper reviewed the potential of 3D food printing in nutritional customization and textural modification of personalized food for the elderly with dysphagia. 3D food printing can be used to re-formulate the food ink by combining more than one type of food materials to ensure high calorie and nutrient intake, improve sensory quality, and prevent malnutrition; thus, understanding the functional properties of such macronutrients compounds is essential to design food ink that meets personalized nutrient requirements. Hydrocolloids have been commonly used to modify the desired soft texture and consistent viscoelastic properties of 3D-printed elderly food, as well as improve printability and structural stability. The food standard guidelines have been established and used to categorize texture-modified foods to ensure easy to eat and safe swallowing for the elderly with swallowing difficulties. Finally, the production of personalized food using 3D printing may provide more food options, facilitate safe oral intake, and increase calorie intake to improve the healthy mealtime experience for the elderly.

Cannabis, traditionally used for recreation due to psychoactive compounds in its leaves, flowers, and seeds, has not been thoroughly explored for potential therapeutic benefits. Δ9-trans-Tetrahydrocannabinol, a key cannabinoid in cannabis, causes hallucinogenic effects and delirium symptoms. In contrast, cannabidiol (CBD) does not induce hallucinations and has shown effectiveness in treating symptoms of various rare, incurable diseases. Cannabis exhibits neuroprotective, anti-inflammatory, anti-thrombotic, anti-bacterial, analgesic, and antiepileptic properties, recently attracting more attention. This review aims to summarize comprehensively the impact of cannabis on human health, focusing on endocannabinoids and their receptors. It also delves into recent CBD research advancements, highlighting the compound’s potential medical applications. Overall, this paper provides valuable insights into the prospective development of medical cannabis, with a particular emphasis on CBD.

Neutron star observations, as well as experiments on neutron-rich nuclei, used to motivate one to look at degenerate nuclear matter from its extreme, namely, pure neutron matter. As an important next step, impurities and clusters in dilute neutron matter have attracted special attention. In this paper, we review in-medium properties of these objects on the basis of the physics of polarons, which have been recently realized in ultracold atomic experiments. We discuss how such atomic and nuclear systems are related to each other in terms of polarons. In addition to the interdisciplinary understanding of in-medium nuclear clusters, it is shown that the quasiparticle energy of a single proton in neutron matter is associated with the symmetry energy, implying a novel route toward the nuclear equation of state from the neutron-rich side.

In this paper, molecular dynamics simulations have been employed to investigate the phonon thermal transport in bilayer polycrystalline graphene nanoribbon (pGNR/pGNR), compared with bilayer graphene nanoribbon (GNR/GNR) and pGNR/GNR heterostructure. The interfacial thermal resistance (ITR) of bilayer structures was also calculated using the heat dissipation method. The effects of interlayer interaction, grain size, and vacancy defects on ITR and in-plane phonon thermal conductivity of bilayer structures were investigated. It was found that the ITR as well as in-plane phonon thermal conductivity of pGNR/pGNR wasless than that of pGNR/GNR and much less than that of GNR/GNR, for the same size. For the studied bilayer structures, both the ITR and in-plane phonon thermal conductivity decrease with increasing interlayer interactions. Moreover, ITR increases with increasing grain area size whereas decreases with increasing vacancy defects in pGNR-based bilayers. The introduction of pGNR interface roughness and vacancy defects results in an enhanced phonon coupling in pGNR-based bilayers compared to pure GNR/GNR bilayers. Presented simulation investigations will help to understand the interlayer thermal transport properties of polycrystalline graphene and provide essential guidance for experimentally regulating phonon thermal transport between layers of polycrystalline graphene.

Bandpass filters with high frequency and wide bandwidth are indispensable parts of the fifth-generation telecommunication technologies, and currently, they are mainly based on surface and bulk acoustic wave resonators. Owing to its high mechanical strength, excellent stability at elevated temperatures, good thermal conductivity, and compatibility with complementary metal-oxide-semiconductor technology, aluminum nitride (AlN) becomes the primary piezoelectric material for high-frequency resonators. This review briefly introduces the structures and key performance parameters of the acoustic resonators. The common filter topologies are also discussed. In particular, research progresses in the piezoelectric AlN layer, electrodes, and substrates of the resonators are elaborated. Increasing the electromechanical coupling constant is the main concern for the AlN film. To synthesize AlN in single-crystalline or poly-crystalline with a high intensity of (0002) orientation, and alloy the AlN with other elements are two effective approaches. For the substrates and bottom electrodes, lattice and thermal expansion mismatch, and surface roughness are critical for the synthesis of a high-crystal-quality piezoelectric layer. The electrodes with low electrical resistance, large acoustic-impedance mismatch to the piezoelectric layer, and low density are ideal to reduce insertion loss. Based on the research progress, several possible research directions in the AlN-based filters are suggested at the end of the paper.

Case management (CM) is an intervention for improving integrated care for patients with complex care needs. The implementation of this complex intervention often raises opportunities for change and collective leadership has the potential to optimize the implementation. However, the application of collective leadership in real-world is not often described in the literature. This commentary highlights challenges faced during the implantation of a CM intervention in primary care for people with complex care needs, including stakeholders’ buy-in and providers’ willingness to change their practice, selection of the best person for the case manager position and staff turnover. Based on lessons learned from PriCARE research program, this paper encourages researchers to adopt collective leadership strategies for the implementation of complex interventions, including promoting a collaborative approach, fostering stakeholders’ engagement in a trusting and fair environment, providing a high level of communication, and enhancing collective leadership attitudes and skills. The learnings from the PriCARE program may help guide researchers for implementing complex healthcare interventions.

Background: The National Cancer Institute’s (NCI) Cancer Center Support Grants (CCSGs) encourages Cancer Centers to address health disparities and reduce the cancer burden in their Catchment Area (CA) through an organized Community Outreach and Engagement (COE) structure. This paper shares the development of two guide models that fosters the operations of the Mayo Clinic Comprehensive Cancer Center (MCCCC) COE Office and programs, the MCCCC COE Impact Model and the MCCCC COE Logic Model. Methods: Following a less than stellar CCSG rating for COE in 2018, the MCCCC developed a transition team to specifically address the critique and create a transformative plan for engaging communities to address cancer burden in the CA. A qualitative research approach was employed, focusing on organizing and displaying the relationship between MCCCC COE processes and outcomes through impact and logic models. An impact model was developed to illustrate the components of the CCSG and connect those components to short- and long-term COE outcomes. A logic model was developed to track and monitor activities for continuous process improvement for all COE activities. Results: The impact and logic model serve as a roadmap to monitor progress towards short- and long-term COE goals of the MCCCC. The COE operational strategies draw upon bidirectional partnership, evidence-based practices, and research facilitation to respond to the CCSG critique. Conclusion: These strategies demonstrate successful practices in addressing cancer burden, promoting health equity and eliminating cancer disparities in the MCCCC CA.

Background: During the COVID-19 pandemic, the field of infodemic management has grown in response to urgent global need. Social listening is the first step in managing the infodemic, and many organizations and health systems have implemented processes. Social media analysis tools have traditionally been developed for commercial purposes, rather than public health, and little is known of the experiences and needs of those professionals using them for infodemic management. Methods: We developed a cross sectional survey and distributed through global infodemic management networks between December 2022 and February 2023. Questions were structured over four sections related to work-practice and user needs and did not collect any personal details from participants. Descriptive analysis was conducted on the study results. Qualitative analysis was used to categorise and understand answers to open-text questions. Results: There were 417 participants, 162/417 who completed all survey questions, and 255/417 who completed some, all responses are included in analysis. Respondents came from all global regions and a variety of workplaces. Participants had an average of 4.4 years’ experience in the analysis of social media for public health. COVID-19 was the most common health issue people had conducted social media analysis for. Results reveal a range of training, technical capacity, and support needs. Conclusions: This paper is the first we are aware of to seek and describe the needs of those using social media analysis platforms for public health purposes since the start of the COVID-19 pandemic. There are key areas for future work and research, including addressing the training, capacity building and leadership needs of those working in this space, and the need to facilitate easier access to better platforms for performing social media analysis.

Background: The COVID-19 pandemic highlights vaccination’s critical role in reducing morbidity and mortality, depending on public attitude. This study aims to identify the estimates of COVID-19 vaccine acceptance in pregnant and lactating women, as well as associated potential factors. Methods: A cross-sectional study was conducted between August and September 2021, through an online survey and with a paper survey distributed in gynecology and pediatric clinics. Pregnant and breastfeeding women aged 18 years and above were recruited. The attitude scale was created specifically for evaluating attitudes towards the COVID-19 vaccine. Results: In total, 207 women participated, with 132 breastfeeding, 74 pregnant and 1 experiencing both conditions. Of these, one hundred and twenty women (58%) considered themselves at risk for COVID-19 infection. In addition, 51.7% (n= 107) of women expressed the intent to receive the vaccine once available. A multivariable linear regression was conducted taking the COVID-19 vaccination attitude scale as a dependent variable. The results revealed an R-squared value of 0.558, indicating that approximately 55.8% of the variance in the attitude scale was accounted for by the included predictors. The results showed that preventive measures (ß=2.25, 95% Confidence Interval (CI) [1.02; 3.48], p< 0.001), preference for vaccines made in Europe and America (ß=1.23; 95% CI [0.69–1.77], p< 0.001), protect yourself for getting sick (ß=4.22, 95% Confidence Interval (CI) [2.83; 5.61], p< 0.001) and belief in the importance of vaccination for themselves and their baby (ß=3.49; 95% CI [2.01; 4.98], p< 0.001) were associated with a positive attitude towards vaccination. Conversely, experiencing a previous bad reaction to a vaccine (ß= -1.35; 95% CI [0.85–1.85], p< 0.001) and concerns regarding COVID-19 vaccine safety (ß= -4.09; 95% CI [-5.98; -2.21], p< 0.001) were associated with a negative attitude towards vaccination. Conclusion: Our findings reveal that COVID-19 vaccine acceptability among pregnant and breastfeeding women, amidst the pandemic was insufficient to meet community immunity. The identified reasons for vaccine reluctance, notably concerns about safety for both personal health and the health of their pregnancy or newborns, along with insufficient information about the vaccine, underscore the pressing need to address these factors to improve immunization rates.

The presence of polycyclic aromatic hydrocarbons (PAHs) in the atmosphere has been linked to health concerns, including cancer. Automobile workshops are significant contributors to PAH emissions due to their operations. Hence, this investigation aimed to identify and quantify the sources of PM2.5-bound PAHs in the ambient air of automobile workshops in Benin City, Nigeria, using molecular diagnostic ratios. PM2.5 samples were collected from 60 automobiles over 1 year, during the rainy (April to November) and dry (December to March) seasons of 2019. Sample collection utilized a low-volume air sampler with quartz filter paper, and extraction was performed using a 1:1 mixture of acetone and dichloromethane. The analysis involved an HP Agilent Technology 6890 Gas Chromatography (GC) system with a flame ionization detector. The annual average concentrations of PM2.5-bound PAHs in Benin City were 269.87 ± 249.32 ng/m3(dry season) and 216.30 ± 204.89 ng/m3(wet season). Molecular diagnostic ratios, such as Fl/(Fl + Py), An/(An + Phe), BaP/(BaP + Chry), BbF/BkF, InP/(InP + BghiP), and BaA/(BaA + Chr), aided in identifying PAH sources. Gasoline combustion, diesel combustion, traffic emissions, and emissions from automobile panel welders were found to be the primary sources of PAHs near vehicle workshops. These findings provide crucial insights for developing effective strategies to reduce emissions and protect public health in the air surrounding automobile workshops in Benin City.

Background: Numerical methods are used to solve differential equations, but few are effective for nonlinear ordinary differential equations (ODEs) of order higher than one. This paper proposes a new method for such ODEs, based on Taylor series expansion. The new method is a second-order method for second-order ODEs, and it is equivalent to the central difference method, a well-known method for solving differential equations. The new method is also simple to implement for higher-order differential equations. The proposed technique was applied to solve the Van der Pol and Van der Pol–Duffing equations. It is stable over a wide range of nonlinearity and produces accurate and reliable results. For the self-excitation Van der Pol equation, the proposed technique was applied with different values of nonlinear damping. Results: The results were compared with those obtained using the ODE15s solver in MATLAB. The two sets of results showed excellent agreement. For the forced Van der Pol–Duffing equation, the proposed technique was applied with different values of exciting force amplitude and frequency. It was found that for certain conditions, the solution obtained using the proposed technique differed from that obtained using ODE15s. Conclusions: The solution obtained using the proposed technique showed good agreement with the solutions obtained using ODE45 and Runge–Kutta fourth order. The results show that the proposed approach is very simple to apply and produces acceptable error. It is a powerful and versatile tool for solving of high-order nonlinear differential equations accurately.

Background: The utilization of Finite Element Analysis (FEA) has emerged as a crucial methodology in the field of structural and elasticity analysis, facilitating researchers in their understanding of material responses to diverse thermal or structural loads. This study investigates the utilization of FEA to simulate the Impact characteristics of titanium composites, with specific emphasis on the Charpy impact test. The research utilizes the Abaqus Explicit software, which is widely recognized for its explicit dynamic analysis functionalities, to simulate high-speed and short-duration events such as impacts. The primary objective of this study is to examine the impact behavior of Ti–7Al–1mo/TiN composites fabricated through the spark plasma sintering technique. The impact behavior is simulated using FEA, wherein the shear failure model is utilized to replicate fracture phenomena. This paper examines the methodology employed in the FEA approach, with a particular focus on various factors including boundary conditions, explicit dynamic analysis settings, and material properties. Results: The outcomes and analyses involve the examination of the von Mises stress distribution, displacement magnitude, and energy behavior of the models that were tested. Reinforcement of Ti–Al–Mo ternary alloy with TiN led to a progressive increase in maximum von Mises stress, reaching a peak at 3 wt% TiN. Conversely, displacement magnitude decreased with increasing TiN content, with CP-Ti and the unreinforced alloy exhibiting the highest values. Absorbed energy also declined with higher TiN levels. While models containing 5 and 7 wt% TiN displayed limited plastic deformation before fracture, composites with ≤ 3 wt% TiN maintained acceptable ductility despite enhanced strength and stiffness. Conclusion: The FEA methodology effectively simulates the Charpy impact characteristics of Ti–7Al–1Mo/TiN composites, thereby offering significant contributions to understanding their mechanical behaviors. These findings suggest that TiN reinforcement up to 3 wt% presents a promising strategy for improving the mechanical performance of Ti–Al–Mo alloys while minimizing the trade-off in toughness. This research emphasizes the inherent trade-off between toughness and strength/stiffness, suggesting the possibility of optimizing the composition of materials to suit particular applications. This study makes a valuable contribution to the expanding field of impact behavior research, demonstrating the potential of FEA, specifically utilizing Abaqus Explicit software, for enhancing material design and evaluation.

Biochar obtained from mixed paper fiber sludge and the grain husks resulted in a significant increase of SOC over 7 years.Biochar aging resulted in a decrease in pH one year after its application in 2015 and 2019.The combination of N-fertilizer with biochar caused an improvement in soil inorganic N content in 2014 and reapplication in 2018.

Functional magnetic resonance imaging (fMRI) provides insights into complex patterns of brain functional changes, making it a valuable tool for exploring addiction-related brain connectivity. However, effectively extracting addiction-related brain connectivity from fMRI data remains challenging due to the intricate and non-linear nature of brain connections. Therefore, this paper proposed the Graph Diffusion Reconstruction Network (GDRN), a novel framework designed to capture addiction-related brain connectivity from fMRI data acquired from addicted rats. The proposed GDRN incorporates a diffusion reconstruction module that effectively maintains the unity of data distribution by reconstructing the training samples, thereby enhancing the model’s ability to reconstruct nicotine addiction-related brain networks. Experimental evaluations conducted on a nicotine addiction rat dataset demonstrate that the proposed GDRN effectively explores nicotine addiction-related brain connectivity. The findings suggest that the GDRN holds promise for uncovering and understanding the complex neural mechanisms underlying addiction using fMRI data.

Sleep stage classification is a necessary step for diagnosing sleep disorders. Generally, experts use traditional methods based on every 30 seconds (s) of the biological signals, such as electrooculograms (EOGs), electrocardiograms (ECGs), electromyograms (EMGs), and electroencephalograms (EEGs), to classify sleep stages. Recently, various state-of-the-art approaches based on a deep learning model have been demonstrated to have efficient and accurate outcomes in sleep stage classification. In this paper, a novel deep convolutional neural network (CNN) combined with a long short-time memory (LSTM) model is proposed for sleep scoring tasks. A key frequency domain feature named Mel-frequency Cepstral Coefficient (MFCC) is extracted from EEG and EMG signals. The proposed method can learn features from frequency domains on different bio-signal channels. It firstly extracts the MFCC features from multi-channel signals, and then inputs them to several convolutional layers and an LSTM layer. Secondly, the learned representations are fed to a fully connected layer and a softmax classifier for sleep stage classification. The experiments are conducted on two widely used sleep datasets, Sleep Heart Health Study (SHHS) and Vincent’s University Hospital/University College Dublin Sleep Apnoea (UCDDB) to test the effectiveness of the method. The results of this study indicate that the model can perform well in the classification of sleep stages using the features of the 2-dimensional (2D) MFCC feature. The advantage of using the feature is that it can be used to input a two-dimensional data stream, which can be used to retain information about each sleep stage. Using 2D data streams can reduce the time it takes to retrieve the data from the one-dimensional stream. Another advantage of this method is that it eliminates the need for deep layers, which can help improve the performance of the model. For instance, by reducing the number of layers, our seven layers of the model structure takes around 400 s to train and test 100 subjects in the SHHS1 dataset. Its best accuracy and Cohen’s kappa are 82.35% and 0.75 for the SHHS dataset, and 73.07% and 0.63 for the UCDDB dataset, respectively.

In the countryside, where intensive rural development and rising property values have been observed since the late 1970s, the preservation and meaning of traditional dwellings have emerged as crucial considerations in shaping Hong Kong’s countryside conservation policy. The focus of this paper is on the conservation of temples, as we are drawn to these structures not only for their architectural merit but also for their role as public buildings within the countryside. Consequently, their cultural significance is heavily influenced by the stakeholders they are associated with, distinguishing them from other types of dwellings.

This paper discusses the cocreation of an emergent place-identity in a Hakka household in the Hong Kong countryside triggered by architectural restoration. Located in Kuk Po, a quintessential Hakka village that was established over 300 years ago, Yeung House was restored by the research team under a government-funded initiative to regenerate architectural values. Rebuilt in 1967, Yeung House has experienced decay and evolution over the years. It signifies the adaptive lifestyle of Hakka immigrants through its adapted siting, hybrid tectonics and modernised features. After restoration, Yeung House was repurposed into a base for education and research managed by the three house-owning villagers. Different activities were initiated by the villagers and coarranged by the research team. As a serendipitous outcome, the front yard of Yeung House has been activated into a multifunctional communal space. Subsequently, it is argued that a place-identity has emerged in Ng To and is influenced by the distinctiveness of the restored Yeung House and the continuity of the front yard. New meanings of the place have been created by the villagers through the practice of a potential, alternative lifestyle in the rural-urban parallel.

This paper aims to establish a unified typology for the culturally significant kullastone houses built in the cross-border region of Kosovo, Albania, and Montenegro during the 18th and 19th centuries. Despite some attempts at typological categorisation on the national level, a joint typology for this region currently needs to be improved. Based on existing literature and field research, the paper identifies the specificities of different geographical locations while validating the core attributes common to all typological variations. The findings suggest that the joint typological classification of kullain the Balkans should primarily be based on architectural elements and, to some extent, setting, building materials and techniques, while functional composition is consistent across all types. The paper argues that defining a common typology for the Albanian kullastone houses in the Balkans is crucial for evaluating, preserving, and developing kullaas serial properties and for their future regional development.

The main purpose of this paper is to explore how the conceptualisation and management of cultural heritage have been treated in the cultural heritage proclamations of Ethiopia. The analysis of the four cultural heritage proclamations reveals that the notion of cultural heritage improves from the first to the fourth proclamation. In the first two proclamations, the term antiquity was employed, and the latter two employed the term of cultural heritage. The 1966 proclamation included antiquities that were dated prior to 1850 EC, while the 1989 proclamation removed this cutoff date and expounded upon the definition of antiquities. The 2000 proclamation replaced the term antiquity with cultural heritage and introduced the concept of intangible cultural heritage. In terms of the management of cultural heritage, the differences between the 1989 and 2000 proclamations are quite minimal. The 2014 proclamation attempted to classify cultural heritage into national and regional cultural heritage. It also defined important components of intangible cultural heritage. The management of cultural heritage exhibits some evolution from the first to the last proclamation. However, due to the diversified nature of cultural heritage conceptualisation and management, it will be important for additional legislation to be issued separately for movable, immovable and intangible cultural heritage, for example. This study argues that strong legal and institutional frameworks should be established to properly protect, conserve and study cultural heritage.

GRPR is a type of seven-transmembrane G-protein coupled receptor that belongs to the bombesin protein receptor family. It is highly expressed in various cancers, including prostate cancer, breast cancer, lung cancer, gastrointestinal cancer, and so on. As a result, molecular imaging studies have been conducted using radiolabeled GRPR ligands for tumor diagnosis, as well as monitoring of recurrence and metastasis. In this paper, we provided a comprehensive overview of relevant literature from the past two decades, with a specific focus on the advancements made in radiolabeled GRPR ligands for imaging prostate cancer and breast cancer.

Background: Breast cancer is the most common cause of cancer-related deaths among women globally and the most deadly illness for them. New advances in nanotechnology have led to the development of strategies intended to target breast cancer cells more precisely while causing the least amount of damage to healthy cells. We retrieved articles about nanomaterials for the diagnosis and treatment of breast cancer from the Web of Science Core Collection (WoSCC) database between 2008 and 2023. Our research aims to assess publications on the use of nanomaterials for breast cancer treatment and diagnosis to predict future research directions. Results: A total of 457 papers on nanomaterials in breast cancer were discovered from various nations, with China being the primary source and the United States having the highest H index. The number of papers in this discipline is increasing on an annual basis. The Egyptian Knowledge Bank is an important research center in this sector. The International Journal of Nanomedicinehas the most papers, and Kesharwani P is the most frequently referenced author. The most quoted article was written by Miele, Evelina of India in 2009. Topics such as drug delivery may be emerging areas of research. Conclusion: Our findings predict that the use of nanomaterials in medication delivery will become a significant research area in the future, and provide valuable references for scholars investigating the role of nanotechnology in breast cancer.

The state of New York admitted 143 million metric tons of carbon emissions from fossil fuels in 2020, prompting the ambitious goal set by the CLCPA to achieve carbon neutrality. The paper focused on analyzing and predicting carbon emissions using four different machine-learning algorithms. It examined emissions from fossil fuel combustion from 1990 to 2020 and validated four different algorithms to choose the most effective one for predicting emissions from 2020 to 2050. The analysis covered various economic sectors including transportation, residential, commercial, industrial, and electric power. By analyzing policies, the paper forecasted emissions for 2030 and 2050, leading to the identification of different pathways to reach carbon neutrality. The research concluded that in order to achieve neutrality, radical measures must be taken by the state of New York. Additionally, the paper compared the most recent data for 2021 with the forecasts, showing that significant measures need to be implemented to achieve the goal of carbon neutrality. Despite some studies assuming a trend of decreased emissions, the research revealed different results. The paper presents three pathways, two of which follow the ambitious plan to reach carbon neutrality. As a result, the emission amount by 2050 for the different pathways was projected to be 31.1, 22.4, and 111.95 of MMt CO2e, showcasing the need for urgent action to combat climate change.

This paper proposes a modified iterative learning control (MILC) periodical feedback-feedforward algorithm to reduce the vibration of a rotor caused by coupled unbalance and parallel misalignment. The control of the vibration of the rotor is provided by an active magnetic actuator (AMA). The iterative gain of the MILC algorithm here presented has a self-adjustment based on the magnitude of the vibration. Notch filters are adopted to extract the synchronous (1 × Ω) and twice rotational frequency (2 × Ω) components of the rotor vibration. Both the notch frequency of the filter and the size of feedforward storage used during the experiment have a real-time adaptation to the rotational speed. The method proposed in this work can provide effective suppression of the vibration of the rotor in case of sudden changes or fluctuations of the rotor speed. Simulations and experiments using the MILC algorithm proposed here are carried out and give evidence to the feasibility and robustness of the technique proposed.

Accurate trajectory prediction of surrounding road users is the fundamental input for motion planning, which enables safe autonomous driving on public roads. In this paper, a safe motion planning approach is proposed based on the deep learning-based trajectory prediction method. To begin with, a trajectory prediction model is established based on the graph neural network (GNN) that is trained utilizing the INTERACTION dataset. Then, the validated trajectory prediction model is used to predict the future trajectories of surrounding road users, including pedestrians and vehicles. In addition, a GNN prediction model-enabled motion planner is developed based on the model predictive control technique. Furthermore, two driving scenarios are extracted from the INTERACTION dataset to validate and evaluate the effectiveness of the proposed motion planning approach, i.e., merging and roundabout scenarios. The results demonstrate that the proposed method can lower the risk and improve driving safety compared with the baseline method.

The most widely adopted method for diagnosing respiratory infectious diseases is to conduct polymerase chain reaction (PCR) assays on patients’ respiratory specimens, which are collected through either nasal or oropharyngeal swabs. The manual swab sampling process poses a high risk to the examiner and may cause false-negative results owing to improper sampling. In this paper, we propose a pneumatically actuated soft end-effector specifically designed to achieve all of the tasks involved in swab sampling. The soft end-effector utilizes circumferential instability to ensure grasping stability, and exhibits several key properties, including high load-to-weight ratio, error tolerance, and variable swab-tip stiffness, leading to successful automatic robotic oropharyngeal swab sampling, from loosening and tightening the transport medium tube cap, holding the swab, and conducting sampling, to snapping off the swab tail and sterilizing itself. Using an industrial collaborative robotic arm, we integrated the soft end-effector, force sensor, camera, lights, and remote-control stick, and developed a robotic oropharyngeal swab sampling system. Using this swab sampling system, we conducted oropharyngeal swab-sampling tests on 20 volunteers. Our Digital PCR assay results (RNase P RNA gene absolute copy numbers for the samples) revealed that our system successfully collected sufficient numbers of cells from the pharyngeal wall for respiratory disease diagnosis. In summary, we have developed a pharyngeal swab-sampling system based on an “enveloping” soft actuator, studied the sampling process, and implemented whole-process robotic oropharyngeal swab-sampling.

Four-wheel independently driven electric vehicles (FWID-EV) endow a flexible and scalable control framework to improve vehicle performance. This paper integrates the torque vectoring and active suspension system (ASS) to enhance the vehicle’s longitudinal and vertical motion control performance. While the nonlinear characteristic of the tire model leads to a relatively heavier computational burden. To facilitate the controller design and ease the load, a half-vehicle dynamics system is built and simplified to the linear-time-varying (LTV) model. Then a model predictive controller is developed by formulating the objective function by comprehensively considering the safety, energy-saving and comfort requirements. The in-wheel motor efficiency and the power loss of tire slip are treated as optimization indices in this work to reduce energy consumption. Finally, the effectiveness of the proposed controller is verified through the rapid-control-prototype (RCP) test. The results demonstrate the enhancement of the energy-saving as well as comfort on the basis of vehicle stability.

The lower limb exoskeletons are used to assist wearers in various scenarios such as medical and industrial settings. Complex modeling errors of the exoskeleton in different application scenarios pose challenges to the robustness and stability of its control algorithm. The Radial Basis Function (RBF) neural network is used widely to compensate for modeling errors. In order to solve the problem that the current RBF neural network controllers cannot guarantee the asymptotic stability, a neural network robust control algorithm based on computed torque method is proposed in this paper, focusing on trajectory tracking. It innovatively incorporates the robust adaptive term while introducing the RBF neural network term, improving the compensation ability for modeling errors. The stability of the algorithm is proved by Lyapunov method, and the effectiveness of the robust adaptive term is verified by the simulation. Experiments wearing the exoskeleton under different walking speeds and scenarios were carried out, and the results show that the absolute value of tracking errors of the hip and knee joints of the exoskeleton are consistently less than 1.5°and 2.5°, respectively. The proposed control algorithm effectively compensates for modeling errors and exhibits high robustness.

The human digital twin (HDT) emerges as a promising human-centric technology in Industry 5.0, but challenges remain in human modeling and simulation. Digital human modeling (DHM) provides solutions for modeling and simulating human physical and cognitive aspects to support ergonomic analysis. However, it has limitations in real-time data usage, personalized services, and timely interaction. The emerging HDT concept offers new possibilities by integrating multi-source data and artificial intelligence for continuous monitoring and assessment. Hence, this paper reviews the evolution from DHM to HDT and proposes a unified HDT framework from a human factors perspective. The framework comprises the physical twin, the virtual twin, and the linkage between these two. The virtual twin integrates human modeling and AI engines to enable model-data-hybrid-enabled simulation. HDT can potentially upgrade traditional ergonomic methods to intelligent services through real-time analysis, timely feedback, and bidirectional interactions. Finally, the future perspectives of HDT for industrial applications as well as technical and social challenges are discussed. In general, this study outlines a human factors perspective on HDT for the first time, which is useful for cross-disciplinary research and human factors innovation to enhance the development of HDT in industry.

Blank holder force (BHF) is a crucial parameter in deep drawing, having close relation with the forming quality of sheet metal. However, there are different BHFs maintaining the best forming effect in different stages of deep drawing. The variable blank holder force (VBHF) varying with the drawing stage can overcome this problem at an extent. The optimization of VBHF is to determine the optimal BHF in every deep drawing stage. In this paper, a new heuristic optimization algorithm named Jaya is introduced to solve the optimization efficiently. An improved “Quasi-oppositional” strategy is added to Jaya algorithm for improving population diversity. Meanwhile, an innovated stop criterion is added for better convergence. Firstly, the quality evaluation criteria for wrinkling and tearing are built. Secondly, the Kriging models are developed to approximate and quantify the relation between VBHF and forming defects under random sampling. Finally, the optimization models are established and solved by the improved QO-Jaya algorithm. A VBHF optimization example of component with complicated shape and thin wall is studied to prove the effectiveness of the improved Jaya algorithm. The optimization results are compared with that obtained by other algorithms based on the TOPSIS method.

There are lots of researches on fixture layout optimization for large thin-walled parts. Current researches focus on the positioning problem, i.e., optimizing the positions of a constant number of fixtures. However, how to determine the number of fixtures is ignored. In most cases, the number of fixtures located on large thin-walled parts is determined based on engineering experience, which leads to huge fixture number and extra waste. Therefore, this paper constructs an optimization model to minimize the number of fixtures. The constraints are set in the optimization model to ensure that the part deformation is within the surface profile tolerance. In addition, the assembly gap between two parts is also controlled. To conduct the optimization, this paper develops an improved particle swarm optimization (IPSO) algorithm by integrating the shrinkage factor and adaptive inertia weight. In the algorithm, particles are encoded according to the fixture position. Each dimension of the particle is assigned to a sub-region by constraining the optional position range of each fixture to improve the optimization efficiency. Finally, a case study on ship curved panel assembly is provided to prove that our method can optimize the number of fixtures while meeting the assembly quality requirements. This research proposes a method to optimize the number of fixtures, which can reduce the number of fixtures and achieve deformation control at the same time.

An increasing number of researchers have researched fixture layout optimization for thin-walled part assembly during the past decades. However, few papers systematically review these researches. By analyzing existing literature, this paper summarizes the process of fixture layout optimization and the methods applied. The process of optimization is made up of optimization objective setting, assembly variation/deformation modeling, and fixture layout optimization. This paper makes a review of the fixture layout for thin-walled parts according to these three steps. First, two different kinds of optimization objectives are introduced. Researchers usually consider in-plane variations or out-of-plane deformations when designing objectives. Then, modeling methods for assembly variation and deformation are divided into two categories: Mechanism-based and data-based methods. Several common methods are discussed respectively. After that, optimization algorithms are reviewed systematically. There are two kinds of optimization algorithms: Traditional nonlinear programming and heuristic algorithms. Finally, discussions on the current situation are provided. The research direction of fixture layout optimization in the future is discussed from three aspects: Objective setting, improving modeling accuracy and optimization algorithms. Also, a new research point for fixture layout optimization is discussed. This paper systematically reviews the research on fixture layout optimization for thin-walled parts, and provides a reference for future research in this field.

The current research of Charpy impact mainly focuses on obtaining the ductile brittle transition temperature of materials by experiments. Compared with experiments, numerical simulation can study many problems with harsh conditions. However, there are still few studies on the influence of geometric factors such as side grooves. In this paper, the geometry of standard Charpy impact test is designed. Specimens with different widths and side grooves are tested. The finite element model of Charpy impact was established by ABAQUS software. Use test results and simulation results to verify each other. The effects of sample width, side groove depth and side groove bottom fillet on the impact fracture resistance of the sample were studied. The results show that the specimen width is positively correlated with the impact toughness of the specimen. The side groove greatly reduces the impact toughness of the material; the toughness of side groove decreases with the increase of depth; the fracture toughness of side groove decreases with the increase of fillet at the bottom of side groove. The proportion of toughness energy to impact energy of samples was analyzed. The results show that the toughness energy accounts for about 70% of the impact energy of the sample, which has little to do with the geometric characteristics of the sample. This study presents a reliable method for studying Charpy impact tests. The influence of geometric parameters is obtained, which provides a reference method for the study of impact toughness of high toughness materials.

Grinding, a critical precision machining process for difficult-to-cut alloys, has undergone continual technological advancements to improve machining efficiency. However, the sustainability of this process is gaining heightened attention due to significant challenges associated with the substantial specific grinding energy and the extensive heat generated when working with difficult-to-cut alloys, renowned for their exceptional physical and mechanical properties. In response to these challenges, the widespread application of massive coolant in manufacturing industries to dissipate grinding heat has led to complex post-cleaning and disposal processes. This, in turn, has resulted in issues such as large energy consumption, a considerable carbon footprint, and concerns related to worker health and safety, which have become the main factors that restrict the development of grinding technology. This paper provides a holistic review of sustainability in grinding difficult-to-cut alloys, encompassing current trends and future directions. The examination extends to developing grinding technologies explicitly tailored for these alloys, comprehensively evaluating their sustainability performance. Additionally, the exploration delves into innovative sustainable technologies, such as heat pipe/oscillating heat pipe grinding wheels, minimum quantity lubrication, cryogenic cooling, and others. These groundbreaking technologies aim to reduce dependence on hazardous coolants, minimizing energy and resource consumption and carbon emissions associated with coolant-related or subsequent disposal processes. The essence of these technologies lies in their potential to revolutionize traditional grinding practices, presenting environmentally friendly alternatives. Finally, future development trends and research directions are put forward to pursue the current limitation of sustainable grinding for difficult-to-cut alloys. This paper can guide future research and development efforts toward more environmentally friendly grinding operations by understanding the current state of sustainable grinding and identifying emerging trends.

Regarding the lane keeping system, path tracking accuracy and lateral stability at high speeds need to be taken into account especially for commercial vehicles due to the characteristics of larger mass, longer wheelbase and higher mass center. To improve the performance mentioned above comprehensively, the control strategy based on improved artificial potential field (APF) algorithm is proposed. In the paper, time to lane crossing (TLC) is introduced into the potential field function to enhance the accuracy of path tracking, meanwhile the vehicle dynamics parameters including yaw rate and lateral acceleration are chosen as the repulsive force field source. The lane keeping controller based on improved APF algorithm is designed and the stability of the control system is proved based on Lyapunov theory. In addition, adaptive inertial weight particle swarm optimization algorithm (AIWPSO) is applied to optimize the gain of each potential field function. The co-simulation results indicate that the comprehensive evaluation index respecting lane tracking accuracy and lateral stability is reduced remarkably. Finally, the proposed control strategy is verified by the HiL test. It provides a beneficial reference for dynamics control of commercial vehicles and enriches the theoretical development and practical application of artificial potential field method in the field of intelligent driving.

Accurate vehicle dynamic information plays an important role in vehicle driving safety. However, due to the characteristics of high mobility and multiple controllable degrees of freedom of drive-by-wire chassis vehicles, the current mature application of traditional vehicle state estimation algorithms can not meet the requirements of drive-by-wire chassis vehicle state estimation. This paper proposes a state estimation method for drive-by-wire chassis vehicle based on the dual unscented particle filter algorithm, which make full use of the known advantages of the four-wheel drive torque and steer angle parameters of the drive-by-wire chassis vehicle. In the dual unscented particle filter algorithm, two unscented particle filter transfer information to each other, observe the vehicle state information and the tire force parameter information of the four wheels respectively, which reduce the influence of parameter uncertainty and model parameter changes on the estimation accuracy during driving. The performance with the dual unscented particle filter algorithm, which is analyzed in terms of the time-average square error, is superior of the unscented Kalman filter algorithm. The effectiveness of the algorithm is further verified by driving simulator test. In this paper, a vehicle state estimator based on dual unscented particle filter algorithm was proposed for the first time to improve the estimation accuracy of vehicle parameters and states.

Non-penetration laser welding of lap joints in austenitic stainless steel sheets is commonly preferred in fields where the surface quality is of utmost importance. However, the application of non-penetration welded austenitic stainless steel parts is limited owing to the micro bulging distortion that occurs on the back surface of the partial penetration side. In this paper, non-penetration lap laser welding experiments, were conducted on galvanized and SUS304 austenitic stainless steel plates using a fiber laser, to investigate the mechanism of bulging distortion. A comparative experiment of DC01 galvanized steel-Q235 carbon steel lap laser welding was carried out, and the deflection and distortion profile of partially penetrated side of the sheets were measured using a non-contact laser interferometer. In addition, the cold-rolled SUS304 was subjected to heat holding at different temperatures and water quenching after bending to characterize its microstructure under tensile and compressive stress. The results show that, during the heating stage of the thermal cycle of laser lap welding, the partial penetration side of the SUS304 steel sheet generates compressive stress, which extrudes the material in the heat-affected zone to the outside of the back of the SUS304 steel sheet, thereby forming a bulge. The findings of these experiments can be of great value for controlling the distortion of the partial penetrated side of austenitic stainless steel sheet during laser non-penetration lap welding.

Predictive maintenance has emerged as an effective tool for curbing maintenance costs, yet prevailing research predominantly concentrates on the abnormal phases. Within the ostensibly stable healthy phase, the reliance on anomaly detection to preempt equipment malfunctions faces the challenge of sudden anomaly discernment. To address this challenge, this paper proposes a dual-task learning approach for bearing anomaly detection and state evaluation of safe regions. The proposed method transforms the execution of the two tasks into an optimization issue of the hypersphere center. By leveraging the monotonicity and distinguishability pertinent to the tasks as the foundation for optimization, it reconstructs the SVDD model to ensure equilibrium in the model's performance across the two tasks. Subsequent experiments verify the proposed method's effectiveness, which is interpreted from the perspectives of parameter adjustment and enveloping trade-offs. In the meantime, experimental results also show two deficiencies in anomaly detection accuracy and state evaluation metrics. Their theoretical analysis inspires us to focus on feature extraction and data collection to achieve improvements. The proposed method lays the foundation for realizing predictive maintenance in a healthy stage by improving condition awareness in safe regions.

The current gait planning for legged robots is mostly based on human presets, which cannot match the flexible characteristics of natural mammals. This paper proposes a gait optimization framework for hexapod robots called Smart Gait. Smart Gait contains three modules: swing leg trajectory optimization, gait period & duty optimization, and gait sequence optimization. The full dynamics of a single leg, and the centroid dynamics of the overall robot are considered in the respective modules. The Smart Gait not only helps the robot to decrease the energy consumption when in locomotion, mostly, it enables the hexapod robot to determine its gait pattern transitions based on its current state, instead of repeating the formalistic clock-set step cycles. Our Smart Gait framework allows the hexapod robot to behave nimbly as a living animal when in 3D movements for the first time. The Smart Gait framework combines offline and online optimizations without any fussy data-driven training procedures, and it can run efficiently on board in real-time after deployment. Various experiments are carried out on the hexapod robot LittleStrong. The results show that the energy consumption is reduced by 15.9% when in locomotion. Adaptive gait patterns can be generated spontaneously both in regular and challenge environments, and when facing external interferences.

The twin-body plasma arc has the decoupling control ability of heat transfer and mass transfer, which is beneficial to shape and property control in wire arc additive manufacturing. In this paper, with the wire feeding speed as a characteristic quantity, the wire melting control ability of twin-body plasma arc was studied by adjusting the current separation ratio (under the condition of a constant total current), the wire current/main current and the position of the wire in the arc axial direction. The results showed that under the premise that the total current remains unchanged (100 A), as the current separation ratio increased, the middle and minimum melting amounts increased approximately synchronously under the effect of anode effect power, the first melting mass range remained constant; the maximum melting amount increased twice as fast as the middle melting amount under the effect of the wire feeding speed, and the second melting mass range was expanded. When the wire current increased, the anode effect power and the plasma arc power were both factors causing the increase in the wire melting amount; however, when the main current increased, the plasma arc power was the only factor causing the increase in the wire melting amount. The average wire melting increment caused by the anode effect power was approximately 2.7 times that caused by the plasma arc power. The minimum melting amount was not affected by the wire-torch distance under any current separation ratio tested. When the current separation ratio increased and reached a threshold, the middle melting amount remained constant with increasing wire-torch distance. When the current separation ratio continued to increase and reached the next threshold, the maximum melting amount remained constant with the increasing wire-torch distance. The effect of the wire-torch distance on the wire melting amount reduced with the increase in the current separation ratio. Through this study, the decoupling mechanism and ability of this innovative arc heat source is more clearly.

This paper presents an integrated control scheme for enhancing the ride comfort and handling performance of a four-wheel-independent-drive electric vehicle through the coordination of active suspension system (ASS) and anti-lock braking system (ABS). First, a longitudinal-vertical coupled vehicle dynamics model is established by integrating a road input model. Then the coupling mechanisms between longitudinal and vertical vehicle dynamics are analyzed. An ASS-ABS integrated control system is proposed, utilizing an H∞controller for ASS to optimize load transfer effect and a neural network sliding mode control for ABS implementation. Finally, the effectiveness of the proposed control scheme is evaluated through comprehensive tests conducted on a hardware-in-loop (HIL) test platform. The HIL test results demonstrate that the proposed control scheme can significantly improve the braking performance and ride comfort compared to conventional ABS control methods.

Copper particles emitted from braking have become a significant source of environmental pollution. However, copper plays a crucial role in resin-based braking materials. Developing high-performance braking materials without copper has become a significant challenge. In this paper, the resin-based braking materials were filled with fly-ash cenospheres to develop copper-free braking materials. The effects of fly-ash cenospheres on the physical properties, mechanical and friction and wear properties of braking materials were studied. Furthermore, the wear mechanism of copper-free resin-based braking materials filled with fly-ash cenospheres was discussed. The results indicate that the inclusion of fly-ash cenospheres in the braking materials improved their thermal stability, hardness and impact strength, reduced their density, effectively increased the friction coefficient at medium and high temperatures, and enhanced the heat-fade resistance of the braking materials. The inclusion of fly-ash cenospheres contributed to the formation of surface friction film during the friction process of the braking materials, and facilitated the transition of form from abrasive wear to adhesive wear. At 100–350 ℃, the friction coefficient of the optimal formulation is in the range of 0.57–0.61, and the wear rate is in the range (0.29–0.65) × 10−7cm3·N−1·m−1, demonstrating excellent resistance to heat-fade and stability in friction coefficient. This research proposes the use of fly-ash cenospheres as a substitute for environmentally harmful and expensive copper in brake materials, which not only improves the performance of braking materials but also reduces their costs.

Citizenship and residency laws in the Gulf Cooperation Council countries developed during a similar time period, with similar influences, and as a result had common characteristics. In recent years, this has begun to change, with new pathways to permanent residency and citizenship developing in the region. This paper takes a comparative case study approach to analyzing the policy changes in Saudi Arabia, Qatar and the United Arab Emirates, and then explores the implications thereof. Broadening the pathways for permanent residency and citizenship offers opportunities (e.g., reversing financial outflows, increasing domestic investment and savings, attracting foreign direct investment and skilled talent) while it also presents risks (e.g., contesting traditional forms of belonging and entitlement, reducing social cohesion, and creating new forms of inequalities). While new pathways have indeed emerged, these pathways are designed for specific types of people, defined by the criteria or requirements of them. The unique policies of the three countries imply unique directions for the economies, demographic transitions, and socio-political cultures of the region.

This introductory paper, reflecting the Thematic Cluster of four papers, brings together two themes that are important for migration studies: return migration and embedding. Beyond any simplistic assumptions of settlement and permanent integration back into the origin country, following return, or notions of ongoing unfettered mobility back and forth over time, this article knits together data from the cluster papers, focusing on Lithuania and Poland, to explore factors that lead to return, or indeed non-return, and subsequent experiences in the ‘home’ country for those who do return. Moreover, using mixed methods, including longitudinal research, we advance a theoretical framework facilitating an examination of how returnees negotiate their lives in the origin society and whether they intend to stay, or migrate again, through the conceptual lens of embedding. While emphasising agency and effort, embedding also recognises structural constraints that may impede migrants’ expectations and aspirations. Hence, return migration may involve parallel processes of re-embedding but also experiences of dis-embedding as the hoped for return project encounters unexpected obstacles and may result in further migration. In mapping the field of return migration, through the concept of embedding, we focus on the impact of Brexit as ‘an unsettling event’.

Anti-immigrant backlash has emerged in recent years as a considerable threat to democracy. In many countries illiberal and anti-democratic political forces driven in part by anti-immigrant sentiment have damaged or threaten to damage the proper functioning of democratic institutions. Should policymakers try to avert this threat by implementing more restrictive immigration policy? If they do so, they may expose immigrants to unjust exclusion. If they do not, they may risk democratic dysfunction, even democratic failure. I will call this the Democratic Dilemma for immigration policy. In this paper I argue that this is a hard ethical dilemma that does not lend itself to a straightforward resolution. I propose an analytic and evaluative framework for assessing possible policy responses to the Dilemma to aid policymakers’ as well as the public’s ethical judgement.

Based on a qualitative study of Zimbabwean migrants based in South Africa, who regularly remitted goods and money to Zimbabwe between 2010 and 2020, this paper suggests that at a local level, remittances alleviated poverty with very limited if any transformation of the political economy at the national level. Such remittances promoted consumerism without sustainable investment that can structurally transform the economy. In addition, the dependence on remittances entrenches the culture of migration at the local level, which also contributes to or promotes ethno-tribal fissiparity. In rethinking diaspora remittances in the post-Mugabe era, it is advanced that the seemingly intractable economic and political quagmire in Zimbabwe must be resolved to inspire confidence in the diaspora to pull remittances together for a national socio-economic cause and not local-level band-aid accomplishments which remittances currently do.

Individuals who reside in a country without regular authorisation generally find it difficult to access public medical services beyond emergency treatment. Even in countries with universal healthcare, there is often a gap between rights on paper and their implementation. Civil society organisations (CSOs) fill this gap by providing medical services to vulnerable populations, including irregular migrants. What, if any, are the ethical dilemmas that arise for CSO staff when delivering such services in countries with universal healthcare? Under what conditions do these dilemmas arise? And what strategies do CSO staff use to mitigate them? We answer these questions using 40 semi-structured interviews with CSO staff working in two European countries with high levels of irregularity, universal healthcare provisions on paper, and significant differences in approaches and availability of public services for irregular migrants: Italy and Spain. We show that CSO staff providing medical services to irregular migrants in places with universal healthcare coverage face a fundamental dilemma between humanitarianismand equity. CSO staff respond to the humanitarian belief in the value of taking all possible steps to prevent or alleviate human suffering, thus promoting a decent quality of life that includes access to both emergency and non-emergency care. In doing so, however, they run the risk of substituting rather than complementing public provisions, thereby preventing governments from assuming responsibility for these services in the long term. Individuals who acknowledge the existence of this dilemma generally oppose the creation of parallel structures; that is, services specifically developed for irregular migrants outside the public system; while those who ignore it essentially subscribe to a tiered system, giving up on considerations of equity. We argue that CSOs involved in the provision of healthcare to irregular migrants do not simply provide services; they also play an inherently political role.

While major advances have been made over the past years in comparing citizenship laws globally, most measures remain restricted to the law-on-the-books. Knowledge about the implementation of these laws remains limited. This poses the question to what extent these measures correspond with the law as experienced by targeted populations. In order to overcome the implementation gap when comparing and measuring citizenship law globally, this paper addresses the question of how to gain a coherent understanding of implementation. Developing a comprehensive typology, the paper distinguishes three crucial elements of implementation: (1) the entry into force of legal provisions (capturing the applicable state of citizenship law), (2) the interpretation of law (the specific interpretation of legal provisions used by the authorities responsible for their execution), and (3) the application of law (executing legal provisions in practice by the authorities). Subsequently, the paper illustrates how this typology can be applied to the analysis of citizenship law implementation by a case study of dual citizenship acceptance, focusing on the renunciation requirement for naturalisation and dual citizenship treaties. The paper concludes by outlining directions for a comparative research agenda that better corresponds with the lived experience of citizenship laws.