Unaddressed Challenges Research Articles

Refillable PUF authentication protocol for constrained devices

Connected devices are deployed at a rapid rate and in broad domains like home automation or industry, forming the Internet of Things. Those devices need to be secure and trusted to prevent malicious use. However some connected devices are low-cost, memory constrained, power constrained, etc.. This greatly limits the deployment of usual security solutions. As the absence of security is not acceptable, it is necessary to search for lightweight security solutions adapted to such devices. Physical Unclonable Function (PUF) technology can support new lightweight security mechanisms and several lightweight security protocols using this technology have been proposed over the years. Those protocols look promising, however there are still some unaddressed challenges which have slowed down a large scale adoption. This article presents the design of a new authentication protocol for constrained devices which takes into account those challenges. This protocol is implemented on a hardware platform used for connected devices development, which is then used to evaluate the security level and performances of the protocol in a realistic scenario. This evaluation shows that the protocol is secure and can meet industrial time constraints.

Impact of COVID-19 response on public health literacy and communication.

With unaddressed challenges of pandemic with re-emergence of coronavirus disease 2019 (COVID-19) waves, public health literacy and communication have proved to be a prerequisite for effective communication as part of the control strategy. Hence this article addressed the impact of COVID-19 response policies on public health literacy. Considering the rapid transmission of COVID-19, taking lives needs urgent attention from the population›s perspective to be more vigilant about health information and incorporate that into their daily routines. To be responsible and resilient globally, governments and states are formulating different health policies and related plans to prevent and control the spread of the pandemic. This article has recommended short-term measures, including smart focused IEC targeted on vaccination and motivational sessions for health care workers and front line workers. Targeted Long-term measures included healthcare system reforms inclusive of resources, workforce, capacity building with particular focus on lifestyle measures addressing non-communicable disease prevention.

Catalytic Radical Reactions of Unsaturated Sugars

AbstractThe functionalization of unsaturated carbohydrates is a powerful approach for the synthesis of a variety of glycoside derivatives, sugar mimics, and enantiomerically pure molecules. This Review will discuss recently developed catalytic radical methods for the functionalization of glycals, exo‐glycals, and exo‐enes, highlighting the opportunities they offer for new reaction design. While providing new routes for the synthesis of complex carbohydrates, catalytic radical transformations of unsaturated sugars overcome the limitations that typically affect classical protocols, such as the use of stoichiometric oxidants/reductants and hazardous and toxic reagents. Currently unaddressed challenges will also be discussed, suggesting new directions for future work and fostering new methodological developments and applications in the field.

Optimization and Machine Learning Applied to Last-Mile Logistics: A Review

The growth in e-commerce that our society has faced in recent years is changing the view companies have on last-mile logistics, due to its increasing impact on the whole supply chain. New technologies are raising users’ expectations with the need to develop customized delivery experiences; moreover, increasing pressure on supply chains has also created additional challenges for suppliers. At the same time, this phenomenon generates an increase in the impact on the liveability of our cities, due to traffic congestion, the occupation of public spaces, and the environmental and acoustic pollution linked to urban logistics. In this context, the optimization of last-mile deliveries is an imperative not only for companies with parcels that need to be delivered in the urban areas, but also for public administrations that want to guarantee a good quality of life for citizens. In recent years, many scholars have focused on the study of logistics optimization techniques and, in particular, the last mile. In addition to traditional optimization techniques, linked to the disciplines of operations research, the recent advances in the use of sensors and IoT, and the consequent large amount of data that derives from it, are pushing towards a greater use of big data and analytics techniques—such as machine learning and artificial intelligence—which are also in this sector. Based on this premise, the aim of this work is to provide an overview of the most recent literature advances related to last-mile delivery optimization techniques; this is to be used as a baseline for scholars who intend to explore new approaches and techniques in the study of last-mile logistics optimization. A bibliometric analysis and a critical review were conducted in order to highlight the main studied problems, the algorithms used, and the case studies. The results from the analysis allow the studies to be clustered into traditional optimization models, machine learning approaches, and mixed methods. The main research gaps and limitations of the current literature are assessed in order to identify unaddressed challenges and provide research suggestions for future approaches.

Nonwetting Nanostructured Hemostatic Material for Bleeding Control with Minimal Adhesion

AbstractHemostatic materials are widely used for bleeding control. However, existing blood‐absorbing wound dressing materials have two unaddressed challenges, blood loss through the hydrophilic material and strong clot adhesion that prevents gauze removal. Here, a nonwetting nanofiber structured material based on a two‐step spray coating procedure for hemostatic application is developed. Interfacial behaviors at the blood/clot‐material interface are exploited for bleeding control and minimizing wound adhesion. It is shown that this nonwetting material can retain blood within the wound, thus preventing blood loss. The nanofiber structure and kaolin microparticles collectively promote fast clotting to seal the wound and generate point‐to‐point contacts between clot and the nanofiber surface. These point‐to‐point contacts would subsequently be damaged by the interfacial shear induced by clot contraction, generating a peeling force significantly smaller than commercial low‐adherent or fast‐clotting hemostatic products. Its bleeding control and low adhesion properties are verified by in vivo animal experiments. The work therefore provides an efficient hemostatic material with excellent bleeding control and low wound adhesion properties, demonstrating an effective strategy to design advanced hemostatic materials by exploiting the interfacial behaviors.

Diagnostics and prognostics for complex systems: A review of methods and challenges

AbstractDiagnostics and prognostics have a significant role in the reliability enhancement of systems and are focused topics of active research. Engineered systems are becoming more complex and are subjected to miscellaneous failure modes that impact adversely their performability. This ever‐increasing complexity makes fault diagnostics and prognostics challenging for the system‐level functions. A significant number of successes have been achieved and acknowledged in some review papers; however, these reviews rarely focused on application to complex engineered systems nor provided a systematic review of diverse techniques and approaches to address the related challenges. To bridge the gap, this paper first presents a review to systematically cover the general concepts and recent development of various diagnostics and prognostics approaches, along with their strengths and shortcomings for the application of diverse engineered systems. Afterwards, given the characteristics of complex systems, the applicability of different techniques and methods that are capable to address the features of complex systems are reviewed and discussed, and some of the recent achievements in the literature are introduced. Finally, the unaddressed challenges are discussed by taking into account the characteristics of automotive systems as an example of complex systems. In addition, future development and potential research trends are offered to address those challenges. Consequently, this review provides a systematic view of the state‐of‐the‐art and case studies with a reference value for scholars and practitioners.

Robust Deep Learning for IC Test Problems

Numerous machine learning (ML), and more recently, deep-learning (DL)-based approaches, have been proposed to tackle scalability issues in electronic design automation, including those in integrated circuit (IC) test. This article examines state-of-the-art DL for IC test and highlights two critical unaddressed challenges. The first challenge involves identifying fit-for-purpose statistical metrics to train and evaluate ML model performance and usefulness in IC test. Our work shows that current metrics do not reflect how well ML models have learned to generalize and perform in the domain-specific context. From this insight, we propose and evaluate alternative metrics that better capture a model’s likely usefulness in the IC test problem. The second challenge is to choose an appropriate input abstraction so as to enable an ML model to learn robust and reliable features. We investigate how well DL for IC test techniques generalize by exploring their robustness to perturbations that alter a netlist’s structure but do not alter its functionality. This article provides insights into challenges via empirical evaluation of the state-of-the-art and offers guidance for future work.

The "Societalization" of pandemic unpreparedness: lessons from Taiwan's COVID response.

Adopting a Civil Sphere Theory framework, we argue that Taiwan’s efforts at containing COVID-19 resulted from its “societalization” of pandemic unpreparedness, which was triggered by the 2003 SARS outbreak and resumed during the COVID-19 pandemic. Societalization refers to the process through which institutional failures are transformed into societal crises, with the civil sphere mobilized to discuss institutional dysfunctions, push for reforms, and attempt to democratize or otherwise transform institutional cultures. The societalization of pandemic unpreparedness in Taiwan led to reforms of the public health administration and the medical profession, thereby establishing state mechanisms for encouraging early responses and coordinating centralized command during outbreaks, and healthcare infrastructures for coordinating patient transfer and ensuring supplies of personal protective equipment. Reflections upon past uncivil acts among citizens motivated the civil sphere to foster a discourse of interdependence, redefining the boundaries between individual choices and civic virtues. Meanwhile, unaddressed challenges remained, including threats related to Taiwan’s political polarization. Our paper challenges the thesis of “authoritarian advantage,” highlighting how democratic societies can foster social preparedness to respond to crises. By illustrating how societalization can reach temporary closures but become reactivated subsequently, our study extends the theory of societalization by explicating its historical dimension.

Catalytically Generated Vanadium Enolates Formed via Interruption of the Meyer-Schuster Rearrangement as Useful Reactive Intermediates.

Enolate chemistry is one of the most fundamental strategies for the formation of carbon-carbon and carbon-heteroatom bonds. Classically, this has been accomplished through the use of stoichiometric quantities of strong base and cryogenic reaction temperatures. However, these techniques present issues related to enolate regioselectivity and functional group tolerance. While more modern methods utilizing stoichiometric activating agents have overcome some of these limitations, these processes add additional steps and suffer from poor atom economy. While certain classes of highly acidic nucleophiles have enabled the development of elegant and general catalytic solutions to address all of these limitations, functionalizing less acidic nucleophiles remains difficult.To overcome these challenges, we developed an alternative general approach for the formation and subsequent functionalization of metal enolates that leverages catalytic amounts of Lewis acid and entirely avoids the need for exogenous base or stoichiometric additives. To do so, we re-engineered the classical Meyer-Schuster rearrangement, which normally converts propargylic alcohols into α,β-unsaturated carbonyl compounds. By careful control of reaction conditions and by selection of an appropriate vanadium-oxo catalyst, the transient metal enolates formed via the 1,3-transposition of propargylic or allenylic alcohols can be guided away from simple protonation reaction pathways and toward more synthetically productive carbon-carbon, carbon-halogen, and carbon-nitrogen bond-forming processes.By utilizing readily available propargylic and allenylic alcohols as our starting materials and relying on a catalytic 1,3-transposition to generate metal enolates in situ, all issues related to the regioselectivity of enolate formation are resolved. Likewise, utilization of a simple isomerization for enolate formation results in a highly efficient process that can be 100% atom economical. The mild reaction conditions employed also allow for remarkable chemoselectivity. Functional groups not typically conducive to enolate chemistry, such as alkynyl ketones, methyl ketones, free alcohols, and primary alkyl halides, are all well tolerated. Finally, by varying the substitution patterns of the alcohol starting materials, enolates of ketones, esters, and even amides are all accessible.Utilizing this strategy starting from propargylic alcohols, we have developed functionalization reactions that produce highly substituted and geometrically defined α-functionalized α,β-unsaturated carbonyl compounds. Such processes include aldol, Mannich, and electrophilic halogenation reactions, as well as dual catalytic reactions wherein catalytically generated vanadium enolates are trapped with catalytically generated palladium π-allyl electrophiles. In the case of allenylic alcohols, we have developed complementary aldol, Mannich, halogenation, and dual catalytic processes to generate α'-functionalized α,β-unsaturated carbonyl products.The results described in this work showcase the power and generality of our alternative approach to enolate chemistry. Additionally, we point out unaddressed challenges in the field and invite other groups to help innovate in these areas.

Studying Christianity in China: Constructions of an Emerging Discourse, by Naomi Thurston

Through in-depth interviews with nearly fifty leading scholars in Sino-Christian studies and theology inside the PRC and Hong Kong, Naomi Thurston charts the interdisciplinarity, marginality, and variable nature of what it means to study Christianity in China. Set against historical and cultural scholarship charting the growth of Christians and Christianity in recent decades, Thurston’s account is notable for its empirical, intellectual, and insular qualities. Indeed, what she terms Sino-Christian studies or theology is at best a loose amalgamation of scholars scattered across a variety of disciplines and institutions, whose embrace of the term “theologian” is ambivalent, whose training is interdisciplinary, and whose interaction with Chinese churches is often sparse. Although the Christian identity of such scholars is a topic of much scrutiny and contention both within and outside of the field, Thurston argues that these scholars “engage in strategic constructions of marginality” (228), playing the part of intellectual outsiders and exiles, while displaying an increasing openness to personal faith and to theology as a source of public and academic good in China.Thurston’s empirical study will be best appreciated by readers intimately familiar with not just the history of Christianity in China but also the nature of Chinese academic culture and institutional divisions with respect to religious studies, theology, and philosophy. Historians and political scientists will find her in depth and intellectual discussions of Chinese modern political history, “Cultural Christians,” and moral politics enlightening (chapter 4), while sociologists and anthropologists will value her thorough discussion of methodology and subjectivity (chapter 2). Chapters 5, 6, and 7 make the strongest and most distinctive contributions to this intellectual mapping of Sino-Christian studies and theology as Thurston draws from her interview material to construct five typologies of Sino-Christian scholars (chapter 5). Then, through the distinctions she identifies between the senior generation, scholars who emerged in the 1980s and 1990s (chapter 6), and younger scholars (chapter 7), she clarifies some of the overall historical shifts and trends in theological thinking. Whereas senior scholars are more likely to maintain a distance between academic scholarship and personal faith, younger scholars are more likely to combine religious interest and identity.In the penultimate chapter, where Thurston again takes up this theme of marginality for Sino-Christian studies and scholars, she illuminates that unlike Christianity in China, Sino-Christian studies do not simply respond to communal, ethical, and societal voids in post-Mao China. Rather these disciplines must and can cultivate a unique theological space in their dialogues between East and West (203–4) and their aspiration to truthful, public, and Chinese insight into a decidedly interdisciplinary and global conversation.Thurston’s empiricism makes a vital contribution to understanding how Chinese scholars articulate their field from within, what the future of Sino-Christian theology may hold, and how global scholars may participate and engage such scholars more fruitfully. The theme of marginality is widely substantiated by these scholar-insiders and their eagerness to maintain the position of outsider-intellectual and the separation of the ecclesial and academic realms offers an archetypal vision for Sino-Christian studies that conjures some distance and critique from contemporary, subjective, ethnographic methods. On this point, however, I’m disappointed to find the author silent: after a truly sophisticated and insightful discussion of empirical subjectivity on pp. 32-35, the author disengages herself from this important methodological debate, to which the Sino-Christian perspective raises so many stimulating, yet fundamentally unaddressed challenges. For the most part, she fails to engage as a co-constructor in this theological discussion, and the book for all its theological parsing with respect to scholarly identity is quite theologically “lite.” Still, Thurston does justice to her interlocutors: the distinct voices of these scholars leap off the pages, and it is a real triumph to map such a dizzying sea of academics and their idiosyncrasies. What is clear is that Sino-Christian studies’ marginality is hardly a detriment to its intricacy: Thurston succeeds in ascertaining the intellectual and theological depth that transcends intergenerational scholarship in China. This is quite the feat and quite the gift for English readers.

Label-free colorectal cancer screening using deep learning and spatial light interference microscopy (SLIM).

Current pathology workflow involves staining of thin tissue slices, which otherwise would be transparent, followed by manual investigation under the microscope by a trained pathologist. While the hematoxylin and eosin (H&E) stain is well-established and a cost-effective method for visualizing histology slides, its color variability across preparations and subjectivity across clinicians remain unaddressed challenges. To mitigate these challenges, recently we have demonstrated that spatial light interference microscopy (SLIM) can provide a path to intrinsic, objective markers, that are independent of preparation and human bias. Additionally, the sensitivity of SLIM to collagen fibers yields information relevant to patient outcome, which is not available in H&E. Here, we show that deep learning and SLIM can form a powerful combination for screening applications: training on 1,660 SLIM images of colon glands and validating on 144 glands, we obtained a benign vs. cancer classification accuracy of 99%. We envision that the SLIM whole slide scanner presented here paired with artificial intelligence algorithms may prove valuable as a pre-screening method, economizing the clinician's time and effort.

Role of gold nanoparticles in advanced biomedical applications.

Gold nanoparticles (GNPs) have generated keen interest among researchers in recent years due to their excellent physicochemical properties. In general, GNPs are biocompatible, amenable to desired functionalization, non-corroding, and exhibit size and shape dependent optical and electronic properties. These excellent properties of GNPs exhibit their tremendous potential for use in diverse biomedical applications. Herein, we have evaluated the recent advancements of GNPs to highlight their exceptional potential in the biomedical field. Special focus has been given to emerging biomedical applications including bio-imaging, site specific drug/gene delivery, nano-sensing, diagnostics, photon induced therapeutics, and theranostics. We have also elaborated on the basics, presented a historical preview, and discussed the synthesis strategies, functionalization methods, stabilization techniques, and key properties of GNPs. Lastly, we have concluded this article with key findings and unaddressed challenges. Overall, this review is a complete package to understand the importance and achievements of GNPs in the biomedical field.

Transports of Sick Neonates to a Tertiary Care Hospital: Condition at Arrival and Outcomes

Objective: To evaluate the transport system, condition of the baby on arrival, and the outcome of the sick neonates transported to our hospital. Methodology: This prospective study included 100 neonates referred to our hospital. A pro forma with a questionnaire regarding the transport details was filled with information taken from the parents/attendant accompanying the baby. Results: A total of 100 number of referrals over a period of 8 months were included. Almost half the referrals were in the first week of life: 74% were term and 26% preterm. Only 28% of the babies were sent with prior communication to our hospital. About 69% babies had a referral document of them, but only 26% had complete information regarding the baby’s illness and prior treatment. The modes of transport used were private ambulance (36%), car (25%), and government ambulance (22%). Few newborns were brought by autorickshaw (12%), bus (3%), and two-wheeler (2%) too. None of the babies were brought with kangaroo mother care (KMC) during transit. Intratransport care included supplemental oxygen (53%) and IV medications (14%). On arrival the transported neonates had problems such as prolonged capillary filling time (78%), hypothermia (72%), respiratory distress (23%), hypoglycemia (14%), needing life support (14%), and apnea (8%). Out of them, 85% improved, 12% were discharged against medical advice, 2% died, and 1% referred. Conclusion: The study highlights the unaddressed challenges and the scope for improving the transport of sick neonates between hospitals and further emphasizes the need for devising solutions.

Vision-Based Approaches for Automatic Food Recognition and Dietary Assessment: A Survey

Consuming the proper amount and right type of food have been the concern of many dieticians and healthcare conventions. In addition to physical activity and exercises, maintaining a healthy diet is necessary to avoid obesity and other health-related issues, such as diabetes, stroke, and many cardiovascular diseases. Recent advancements in machine learning applications and technologies have made it possible to develop automatic or semi-automatic dietary assessment solutions, which is a more convenient approach to monitor daily food intake and control eating habits. These solutions aim to address the issues found in the traditional dietary monitoring systems that suffer from imprecision, underreporting, time consumption, and low adherence. In this paper, the recent vision-based approaches and techniques have been widely explored to outline the current approaches and methodologies used for automatic dietary assessment, their performances, feasibility, and unaddressed challenges and issues.

Environmental Law in the Time of Climate Change: Towards Integrative Environmental Law

As the magnitude of the threat posed by climate change has become increasingly apparent, scholars and practitioners have begun a dialogue about how to reform environmental law to meet the challenge. Concepts like adaptive management, sustainability, and resilience have emerged in succession, as policy makers and scholars search for new moorings for our ethical and legal framework. While useful, these concepts have failed to provide a vision, goal, or solid ethical grounding for environmental law in the era of climate change. This project takes a new approach by exploring what we can learn from the field of Integrative Medicine. The history of the development of Integrative Medicine offers interesting parallels, contrasts, and lessons for environmental law as it grapples with the existential challenges of climate change. The article highlights the striking similarities between the limitations of conventional medicine that led doctors to pursue an integrative approach and the limitations that have stymied progress under our environmental laws. After reviewing developments in environmental law and policy that align with a path towards an integrative approach, it outlines the key unaddressed challenges, and prescribes a path towards integrative environmental law. It describes how these reforms grounded in lessons from Integrative Medicine will help us to better meet the challenges of climate change. In closing, it offers several case studies of ongoing law and policy advocacy that illustrate how an integrative approach can overcome the limitations that have impeded our progress in addressing climate change and other environmental challenges.

Freestanding hierarchical vascular structures engineered from ice

The ability to engineer a synthetic hierarchical vascular network is one of the most demanding and unaddressed challenges in tissue engineering and regenerative medicine. A material that is both structurally rigid and biocompatible is needed to fabricate freestanding hierarchical vascular structures with defined dimensions and geometry. This is particularly important for creating commercially viable and easily suturable synthetic vasculature. Here, we present the surprising discovery that ice is a versatile material which satisfies these requirements. We demonstrate utilizing ice as a sacrificial scaffold, onto which a diverse range of materials were coated, including tropoelastin, polycaprolactone (PCL), silk, and polydimethylsiloxane (PDMS). We present ice facilitating the fabrication of freestanding hierarchical vascular structures with variable lumen dimensions, and validate the vascular application of these vessels by demonstrating their mechanical tunability, biocompatibility, and permeability to nutrient diffusion. This adaptable technology delivers engineered synthetic vasculature and has potential wider applications encompassing tissue engineering bespoke structures.

The development of a district nursing caseload review tool.

District Nursing (DN) caseloads are increasingly unwieldy. ( Queen's Nursing Institute, 2016 ). They can also be difficult to manage due to the unpredictability and increasing complexity of the patient's needs. It is an essential component of DN teams that caseloads are reviewed on a regular basis to support the delivery of efficient, effective and safe patient care. This article illustrates how a caseload review tool was developed, which would standardise the process in all teams, analyse and monitor the outcomes, identify any trends and themes and give assurance that DN caseloads were productive and safe. The testing, piloting and evaluation of the DN caseload review tool was over a period of 12 months and included 35 DN teams across the Trust. The method used was standardised and systematic, in order to ensure that the results were consistent across the pilot site. It also allowed for standardised challenges to be made by the reviewers, ensuring that the process was efficient and meaningful, the outcomes measured and documented and the clinical systems updated appropriately. Results from the initial reviews have been positive. They have produced both qualitative and quantitative data, which has supported further development of the tool. In addition, actions and outcomes identified for individual patients have been documented and addressed, where possible, at local level. A governance process is in place which supports unaddressed challenges, themes and trends. The conclusion of the pilot has confirmed that this process is valid and will continue to be used within the organisation.

The development of a district nursing caseload review tool.

District Nursing (DN) caseloads are increasingly unwieldy. ( Queen's Nursing Institute, 2016 ). They can also be difficult to manage due to the unpredictability and increasing complexity of the patient's needs. It is an essential component of DN teams that caseloads are reviewed on a regular basis to support the delivery of efficient, effective and safe patient care. This article illustrates how a caseload review tool was developed, which would standardise the process in all teams, analyse and monitor the outcomes, identify any trends and themes and give assurance that DN caseloads were productive and safe. The testing, piloting and evaluation of the DN caseload review tool was over a period of 12 months and included 35 DN teams across the Trust. The method used was standardised and systematic, in order to ensure that the results were consistent across the pilot site. It also allowed for standardised challenges to be made by the reviewers, ensuring that the process was efficient and meaningful, the outcomes measured and documented and the clinical systems updated appropriately. Results from the initial reviews have been positive. They have produced both qualitative and quantitative data, which has supported further development of the tool. In addition, actions and outcomes identified for individual patients have been documented and addressed, where possible, at local level. A governance process is in place which supports unaddressed challenges, themes and trends. The conclusion of the pilot has confirmed that this process is valid and will continue to be used within the organisation.

Understanding the Bioinformatics Challenges of Integrating Genomics into Healthcare.

Genomic data is paving the way towards personalized healthcare. By unveiling genetic disease-contributing factors, genomic data can aid in the detection, diagnosis, and treatment of a wide range of complex diseases. Integrating genomic data into healthcare is riddled with a wide range of challenges spanning social, ethical, legal, educational, economic, and technical aspects. Bioinformatics is a core integration aspect presenting an overwhelming number of unaddressed challenges. In this paper we tackle the fundamental bioinformatics integration concerns including: genomic data generation, storage, representation, and utilization in conjunction with clinical data. We divide the bioinformatics challenges into a series of seven intertwined integration aspects spanning the areas of informatics, knowledge management, and communication. For each aspect, we provide a detailed discussion of the current research directions, outstanding challenges, and possible resolutions. This paper seeks to help narrow the gap between the genomic applications, which are being predominantly utilized in research settings, and the clinical adoption of these applications.

Tree‐Inspired Design for High‐Efficiency Water Extraction

The solar steam process, akin to the natural water cycle, is considered to be an attractive approach to address water scarcity issues globally. However, water extraction from groundwater, for example, has not been demonstrated using these existing technologies. Additionally, there are major unaddressed challenges in extracting potable water from seawater including salt accumulation and long-term evaporation stability, which warrant further investigation. Herein, a high-performance solar steam device composed entirely of natural wood is reported. The pristine, natural wood is cut along the transverse direction and the top surface is carbonized to create a unique bilayer structure. This tree-inspired design offers distinct advantages for water extraction, including rapid water transport and evaporation in the mesoporous wood, high light absorption (≈99%) within the surface carbonized open wood channels, a low thermal conductivity to avoid thermal loss, and cost effectiveness. The device also exhibits long-term stability in seawater without salt accumulation as well as high performance for underground water extraction. The tree-inspired design offers an inexpensive and scalable solar energy harvesting and steam generation technology that can provide clean water globally, especially for rural or remote areas where water is not only scarce but also limited by water extraction materials and methods.