Research Paths Research Articles

Talent agglomeration research within digital economy development: Trend analysis and research prospects

Talent is important for development and innovation across fields. Further, in this era of digital economy, primarily driven by modern information networks, how to attract talent and effectively leverage talent’s agglomeration effect is a crucial research topic. Thus, this paper reviewed studies from the China Knowledge Network in the Chinese Social Sciences Citation Index and from the Web of Science Core Collection. By combining cluster analysis based on keyword co-occurrence with a review of highly relevant literature, this paper determines and compares mainstream directions in both domestic Chinese and international studies on talent agglomeration effects and digital economy talent research, thereby constructing a two-dimensional analytical framework. This paper recommends four research paths for the effects of talent agglomeration, namely, talent management, enterprise–industry development, industry–regional development, and industry–regional level of talent agglomeration. Meanwhile, considering the digital economy’s key role in future national economic strategies, its human resources studies should be included in these same paths for studying talent aggregation effects. Introducing public sector strategic manement theories into research on digital-economic talent aggregation could prove an extremely valuable subject matter in the future.

Knowledge mapping and evolutionary analysis of energy storage resource management under renewable energy uncertainty: a bibliometric analysis

The research on energy storage resource management is an important measure to cope with the present problem of uncertainty in the use of renewable energy, in order to explore the evolution of the research focus and future trend of energy storage resource management under the uncertainty of renewable energy, this paper adopts the method of bibliometric analysis, and conducts a visual analysis of the relevant 800 documents in the core collection of the Web of Science by using the CiteSpace to draw co-occurrence maps and analyze the collaborative networks of different countries/regions, institutions and authors in this field, and further conducted journal co-citation analysis, literature co-citation analysis and author co-citation analysis. The keyword co-occurrence, emergent analysis, and cluster co-occurrence analysis reveal the current research focus and trend in this field, and summarize and propose four future key focus directions: energy storage technology improvement, energy storage system integration, expansion of business models for energy storage resource management, and intelligent control of energy storage system, which provide new research paths for solving the problem of renewable energy uncertainty in the future.

Fueling innovation management research: Future directions and five forward‐looking paths

AbstractResearch about innovation management explores how the future is created—who is creating it (organizations, collaborations, etc.), for what aims (customer satisfaction, market performance, etc.), and with what broader effects (social, environmental, etc.). With this extended essay, we explore the potential futures of innovation management research in three ways. First, we briefly review the history of past research agendas and priorities published in the Journal of Product Innovation Management (JPIM), highlighting three broad topic areas (technological, social/environmental, and organizational) that have emerged over time and their potential disruptive implications for innovation management research. Second, we describe the outcome of a gathering of leading scholars in innovation management tasked with the challenge of identifying critical research paths for our field. This collaboration resulted in five “deep dive” essays into areas ripe for innovation management research in the years ahead: liquid innovation, artificial intelligence in innovation, business model innovation, public value innovation, and responsible innovation. Third, we reflect on this expansive effort and offer a discussion of implications (tensions, challenges, and opportunities) for future innovation management scholarship.

How Does ESG Performance Affect Corporate Financial Performance?

This paper synthesizes the research trends both domestically and internationally on the impact of corporate Environmental, Social, and Governance (ESG) performance on its financial performance. The majority of the studies support a positive correlation between ESG and financial performance, suggesting that ESG practices contribute to sustainable development and enhance corporate financial outcomes. However, the relationship is complex and may be influenced by a variety of factors, including the measurement methods of indicators, the country or region of the research subjects, and the type of industry, leading to divergent conclusions in existing studies. By reviewing the relationship between ESG performance and financial performance, this paper organizes the differences in research subjects and results behind various conclusions, aiming to provide potential research paths for future studies.

Hydrogel Applications in Nitrogen and Phosphorus Compounds Recovery from Water and Wastewater: An Overview

This article provides an overview of the diverse applications of hydrogels in nutrient recovery from water and wastewater. Due to their unique properties, such as high water-retention capacity, nutrient rerelease, and tunable porosity, hydrogels have emerged as promising materials for efficient nutrient capture and recycling. It has been suggested that hydrogels, depending on their composition, can be reused in agriculture, especially in drought-prone areas. Further research paths have been identified that could expand their application in these regions. However, the main focus of the article is to highlight the current gaps in understanding how hydrogels bind nitrogen and phosphorus compounds. The study underscores the need for research that specifically examines how different components of hydrogel matrices interact with each other and with recovered nutrients. Furthermore, it is essential to assess how various nutrient-recovery parameters, such as temperature, pH, and heavy metal content, interact with each other and with specific matrix compositions. This type of research is crucial for enhancing both the recovery efficiency and selectivity of these hydrogels, which are critical for advancing nutrient-recovery technologies and agricultural applications. A comprehensive research approach involves using structured research methodologies and optimization techniques to streamline studies and identify crucial relationships.

Compressive strength detection of tunnel lining using hyperspectral images and machine learning

Traditional tunnel lining strength detection techniques are mostly contact-based, with relatively low detection efficiency. This study innovatively proposes hyperspectral imaging method to rapidly detect tunnel concrete lining strength from a machine vision perspective. Hyperspectral cameras were employed in indoor experiments to capture hyperspectral images of concrete specimens with different compressive strength levels. The differences of concrete strength based on hyperspectral reflectance characteristics were analysed using hyperspectral images and machine learning algorithms. Firstly, the K-Nearest Neighbors (KNN) classification algorithm was used to predict the classification of the concrete hyperspectral dataset with accuracy mostly exceeding 90 %. The results indicate distinctive differences in hyperspectral reflectance characteristics among concrete specimens. Furthermore, compressive strength prediction of different concrete specimens was carried out using Principal component regression (PCR), Partial least squares regression (PLSR), and Least Squares Support Vector Machine (LSSVM) machine learning models on both original and Savitzky-Golay(S-G) processed spectral data. LSSVM and PLSR models performed excellently in the visible light spectrums(400–1000 nm), with LSSVM excelling in the near-infrared spectrums(900–1700 nm). Finally, the feasibility of using Hyperspectral imaging(HSI) technology to detect tunnel lining strength was demonstrated at the shield tunnel model site. The predicted results were validated by combining with strength values measured by the rebound hammer, and presented promoising research path for automated non-destructive detection of concrete tunnel lining strength.

Impacts of water treatments on bacterial communities of biofilm and loose deposits in drinking water distribution systems

Treated drinking water is delivered to customers through drinking water distribution systems (DWDSs). Although studies have focused on exploring the microbial ecology of DWDSs, knowledge about the effects of different water treatments on the bacterial community of biofilm and loose deposits in DWDS is limited. This study assessed the effects of additional treatments on the bacterial communities developed in 10 months’ old pilot DWDSs. The results showed a similar bacterial community in the pipe-wall biofilm, which was dominated by Novosphingobium spp. (20–82 %) and Sphingomonas spp. (11–53 %), regardless of the treatment applied. The bacterial communities that were retained in the distribution systems (including pipe-wall biofilm and loose deposits) were similar to the particle-associated bacteria (PAB) in the corresponding supply water. The additional treatments showed clear effects of the removal and/or introduction of particles. The genera Aeromonas spp., Clostridium spp., Legionella spp., and Pseudomonas spp., which contain opportunistic pathogenic species, were only detected among the PAB in ion exchange system. Our study demonstrated that the biofilm community is consistent across treatments, and the contribution from bacteria in loose deposits is important but can be controlled by removing particles. These findings offer more insight into the origin and development of microbial ecology in DWDSs and suggest paths for further research on the possibility of managing the microbial ecology in distribution systems.

Research on the Path of Natural Research Helping Rural Revitalization — Take Dazhuyuan Village in Anji as an Example

Research on the Path of Natural Research Helping Rural Revitalization — Take Dazhuyuan Village in Anji as an Example

Sentient libraries: empowering user expeditions with emotional artificial intelligence

Purpose The study aims to forecast emotional artificial intelligence’s (EAI) trajectory in libraries, provide actionable implementation recommendations and outline potential research paths. It seeks to establish ethical benchmarks, considering emotional well-being alongside informational needs. Understanding EAI in libraries becomes pivotal, envisioning libraries as empathetic, user-centric spaces. Design/methodology/approach This research uses a multifaceted approach, intertwining comprehensive literature analysis, illustrative case studies and forward-thinking assessments. It combines foundational knowledge from various academic sources, integrating real-world examples of EAI implementations in library settings. The methodology goes beyond observational analysis, scrutinizing ethical quandaries and societal impacts. It comprehensively explains EAI’s role while delineating guidelines for responsible integration and future exploration. Findings Integrating emotional intelligence (EI) enhances resource curation, fosters inclusive virtual learning environments and elevates continuous service enhancement in libraries. It allows tailored recommendations, emotionally perceptive virtual assistants and adaptive responses to diverse emotional needs, reshaping libraries into empathetic spaces. Research limitations/implications Ethical considerations pose significant challenges, especially regarding privacy, security and fair usage of EAI. Libraries must mitigate biases and ensure equitable emotional services. Adapting to diverse emotional needs within library services requires a delicate balance between empathetic approaches and upholding ethical standards. Practical implications EAI revolutionizes user experiences, offering personalized, engaging interactions while ensuring ethical, inclusive library environments. Implementing EAI requires navigating biases and ethical complexities, demanding continuous refinement and using user-focused strategies. Social implications Integrating EAI redefines the library’s role, transforming libraries into emotionally perceptive hubs catering to users’ intellectual and emotional needs. It emphasizes fairness, trust and ethical conduct in providing empathetic, inclusive services. Originality/value This research pioneers the integration of EI in libraries, offering insights into ethical frameworks, bias mitigation and user-centric approaches. It envisions libraries as empathetic, responsive spaces, enriching lives through emotional understanding and responsiveness.

Making sense out of uncertainty: cognitive strategies in the child custody decision-making process.

Child custody cases post-parental separation entail inherent complexities and uncertainties for legal experts and decision-makers, and are influenced by context factors. This study sheds light on how legal actors (i.e., judges, prosecutors, lawyers, psychologists, and social workers) navigate the uncertainties that arise in such context and, therefore, make their decisions. Based on a reflexive thematic analysis involving 73 participants from Brazil and England, this study reveals cognitive strategies employed by legal actors to comprehend uncertainty and operate in the decision-making context. These strategies encompass heuristics (i.e., selection, evaluation, degrees of freedom, and outsourcing decisions/ resolution) and metacognitive strategies (custodial arrangements, professional practices and 'best interests of the child' speech). These results provide a window into the decision-making processes in child custody cases; they offer a comprehensive understanding of the multifaceted sensemaking strategies employed by legal professionals. The results carry substantial implications for informing and improving legal practice in handling complex child custody situations. Furthermore, this study charts new paths for future research by highlighting potential avenues for refining and advancing the strategies employed by legal experts in these cases, especially considering the child's best interests.

Colossal Orbital Current Induced by Gradient Oxidation for High-Efficiency Magnetization Switching.

Orbital angular momentum flow can be used to develop a low-dissipation electronic information device by manipulating the orbital current. However, efficiently generating and fully harnessing orbital currents is a formidable challenge. In this study, an approach is presented that induces a colossal orbital current by gradient oxidation in Pt/Ta to enhance spin-orbit torque (SOT) and achieve high-efficiency magnetization switching. The maximum efficiency of the SOT before and after the gradient oxidation of Ta is improved relative to that of Pt by ≈600 and 1200%, respectively. The large SOT originates from the colossal orbital current because of the orbital Rashba-Edelstein effect induced by the gradient oxidation of Ta. In addition, a large spin-to-charge conversion efficiency is observed in yttrium iron garnet/Pt/TaOx because of the inverse orbital Rashba-Edelstein effect. Harnessing the orbital current can help effectively minimize the critical current density of the current-induced magnetization switching to 2.26-1.08 × 106 Acm-2, marking a 12-fold reduction compared to that using Pt. This findings provide a new path for research on low-dissipation spin-orbit devices and improve the tunability of orbital current generation.

Statistical learning shapes pain perception and prediction independently of external cues.

The placebo and nocebo effects highlight the importance of expectations in modulating pain perception, but in everyday life we don't need an external source of information to form expectations about pain. The brain can learn to predict pain in a more fundamental way, simply by experiencing fluctuating, non-random streams of noxious inputs, and extracting their temporal regularities. This process is called statistical learning. Here, we address a key open question: does statistical learning modulate pain perception? We asked 27 participants to both rate and predict pain intensity levels in sequences of fluctuating heat pain. Using a computational approach, we show that probabilistic expectations and confidence were used to weigh pain perception and prediction. As such, this study goes beyond well-established conditioning paradigms associating non-pain cues with pain outcomes, and shows that statistical learning itself shapes pain experience. This finding opens a new path of research into the brain mechanisms of pain regulation, with relevance to chronic pain where it may be dysfunctional.

Statistical learning shapes pain perception and prediction independently of external cues

The placebo and nocebo effects highlight the importance of expectations in modulating pain perception, but in everyday life we don’t need an external source of information to form expectations about pain. The brain can learn to predict pain in a more fundamental way, simply by experiencing fluctuating, non-random streams of noxious inputs, and extracting their temporal regularities. This process is called statistical learning. Here, we address a key open question: does statistical learning modulate pain perception? We asked 27 participants to both rate and predict pain intensity levels in sequences of fluctuating heat pain. Using a computational approach, we show that probabilistic expectations and confidence were used to weigh pain perception and prediction. As such, this study goes beyond well-established conditioning paradigms associating non-pain cues with pain outcomes, and shows that statistical learning itself shapes pain experience. This finding opens a new path of research into the brain mechanisms of pain regulation, with relevance to chronic pain where it may be dysfunctional.

Breaking the Postmodern Deadlock: Metamodernism’s Methodological Revolution

Abstract This paper is a response to the roundtable on Metamodernism: The Future of Theory, focusing on the work’s methodological implications and theoretical advancements. Using traffic jams as a case study, Jason Ānanda Josephson Storm illustrates how his approach both incorporates and transcends the insights of discourse studies. He abridges a version of his theory of process “social kinds,” which he describes as dynamic, socially constructed clusters of properties, defined by the anchoring processes – dynamic-nominalist, mimetic, and ergonic – that uniquely contribute to their properties. He shows how focusing on these anchoring processes challenges conventional methodologies and could herald new research paths in religious studies and other fields, advocating for a shift towards a more inclusive and dynamic interpretation of social phenomena.

Immunotherapy in Breast Cancer.

Breast cancer is a disease encompassing a spectrum of molecular subtypes and clinical presentations, each with distinct prognostic implications and treatment responses. Breast cancer has traditionally been considered an immunologically "cold" tumor, unresponsive to immunotherapy. However, clinical trials in recent years have found immunotherapy to be an efficacious therapeutic option for select patients. Breast cancer is categorized into different subtypes ranging from the most common positive hormone receptor (HR+), human epidermal growth factor receptor 2 (HER2)-negative type, to less frequent HER2- positive breast cancer and triple-negative breast cancer (TNBC), highlighting the necessity for tailored treatment strategies aimed at maximizing patient outcomes. Despite notable progress in early detection and new therapeutic modalities, breast cancer remains the second leading cause of cancer death in the USA. Moreover, in recent decades, breast cancer incidence rates have been increasing, especially in women younger than the age of 50. This has prompted the exploration of new therapeutic approaches to address this trend, offering new therapeutic prospects for breast cancer patients. Immunotherapy is a class of therapeutic agents that has revolutionized the treatment landscape of many cancers, namely melanoma, lung cancer, and gastroesophageal cancers, amongst others. Though belatedly, immunotherapy has entered the treatment armamentarium of breast cancer, with the approval of pembrolizumab in combination with chemotherapy in triple-negative breast cancer (TNBC) in the neoadjuvant and advanced settings, thereby paving the path for further research and integration of immune checkpoint inhibitors in other subtypes of breast cancer. Trials exploring various combination therapies to harness the power of immunotherapy in symbiosis with various chemotherapeutic agents are ongoing in hopes of improving response rates and prolonging survival for breast cancer patients. Biomarkers and precise patient selection for the utilization of immunotherapy remain cardinal and are currently under investigation, with some biomarkers showing promise, such as Program Death Lignat-1 (PDL-1) Combined Positive Score, Tumor Mutation Burden (TMB), and Tumor Infiltrating Lymphocytes (TILs). This review will present the current landscape of immunotherapy, particularly checkpoint inhibitors, in different types of breast cancer.

Exploring Speech Act Patterns In Anthropological Pragmatics

The purpose of this paper is to look into discourse patterns of President Joe Biden from an anthropological pragmatics perspective, and the theory of speech acts, in particular. I will argue that speech acts are double-edged tools in human communication that have the power to create objective facts accepted and maintained by human agreement on the one hand but are also determined by fluctuating socio-cultural context. In exploring the topic of the American presidency from an anthropological pragmatics perspective, this article addresses theoretical and methodological issues which further our understanding of linguistic structure of social reality determined by socially constrained functions that underlie culture. Thus, this paper argues for a broadened research path to advance the theory of speech acts in political discourse. An analysis of President Joe Biden’s language practices uncovers the rhetorical concept of ethos and its criterion of credibility that is indicative of his presidential status.

The «Cultural Turn» in American Historiography of Environmental History from the 1980s to the Early 2000s: Causes and Consequences

The period since the 1970s has seen a «cultural turn» that affected many areas of historical research. Environmental history is no exception. It emerged in the United States five decades ago and was strongly influenced by intellectual history. However, in the 1990s, the focus of environmental historians gradually shifted towards «new cultural history». Although foreign historiography has repeatedly acknowledged this shift, the underlying reasons that prompted historians to pursue the new research path remain overlooked. This article seeks to bridge the «gap» in the historiography of human interactions with the natural world over time, an important branch of history. The results of a thorough analysis of the major works written by American historians between the 1970s and 2010s show that the «cultural turn» in the American historiography of environmental history was gradual and included two distinct stages. During the first stage, from the 1980s to the mid-1990s, historians explored the problems of environmental history from the perspectives of postcolonial and gender discourses. The second stage, from the mid-1990s to the present day, was marked by a rethinking of the concept of «wilderness», as well as an emphasis on a variety of previously unaddressed problems of environmental history.

Psychological Well-Being From Sports Injuries in Adolescence: A Narrative Review.

The objective of this paper is to review how the mental and psychological well-being of the adolescent athlete population may be impacted by sports injuries, specifically the development of their personal identities. To answer this question, we conducted a narrative review using keywords such as "adolescence," "psychological," "injury," and "sport" in the PubMed database. When conducting the research, we included sources from the past 15 years in order to gain a more present and accurate analysis of our question, and no countries were excluded from our population. Through our research, we identified risk factors that contribute to the rising psychological stress on adolescents. The return to sport was also found to be primarily affected by implied psychological illnesses such as self-confidence and identity, along with parental and coach guidance through the rehabilitation process. Despite the lack of research, scientists work to pursue additional psychological interventions to ensure the emotional well-being of adolescent athletes. Through this review, we aim to inform athletes, coaches, parents, and pediatricians about psychological issues that they may face as they continue to pursue their respective roles in sports. This study also paves a path for future research concerning potential interventions to prevent such psychological issues and ensure both physical and mental health for young athletes.

Metabolic adaptations in prostate cancer.

Prostate cancer is one of the most commonly diagnosed cancers in men and is a major cause of cancer-related deaths worldwide. Among the molecular processes that contribute to this disease, the weight of metabolism has been placed under the limelight in recent years. Tumours exhibit metabolic adaptations to comply with their biosynthetic needs. However, metabolites also play an important role in supporting cell survival in challenging environments or remodelling the tumour microenvironment, thus being recognized as a hallmark in cancer. Prostate cancer is uniquely driven by androgen receptor signalling, and this knowledge has also influenced the paths of cancer metabolism research. This review provides a comprehensive perspective on the metabolic adaptations that support prostate cancer progression beyond androgen signalling, with a particular focus on tumour cell intrinsic and extrinsic pathways.

A comprehensive review of the application of Zr-based metal-organic frameworks for electrochemical sensors and biosensors.

A family of inorganic-organic hybrid crystalline materials made up of organic ligands and metal cations or clusters is known as metal-organic frameworks (MOFs). Because of their unique stability, intriguing characteristics, and structural diversity, zirconium-based MOFs (Zr-MOFs) are regarded as one of the most interesting families of MOF materials for real-world applications. Zr-MOFs that have the ligands, metal nodes, and guest molecules enclosed show distinct electrochemical reactions. They can successfully and sensitively identify a wide range of substances, which is important for both environmental preservation and human health. The rational design and synthesis of Zr-MOF electrochemical sensors and biosensors, as well as their applications in the detection of drugs, biomarkers, pesticides, food additives, hydrogen peroxide, and other materials, are the main topics of this comprehensivereview. We also touch on the current issues and potential future paths for Zr-MOF electrochemical sensor research.