Network Support Research Articles

Automated digital counselling promotes therapeutic change in mental health in patients with chronic heart failure or chronic kidney disease: ODYSSEE-vCHAT study

Abstract Background The efficacy of digital programs to improve the management of chronic heart failure (CHF) and chronic kidney disease (CKD) is not established. Building on related studies in digital health, behavioural counselling, and social support, we evaluated whether an automated digital counselling program with social network support (ODYSSEE-vCHAT) could improve mental health and health-related quality of life in patients with CHF or CKD. Purpose The primary objective was to examine whether engagement with ODYSSEE-vCHAT was associated with a minimal clinically important difference for improvement in the Mental Component Summary (MCS) of the SF-36 at end-of-study. Secondary outcomes included: ENRICHD Social Support Index (ESSI), Patient Health Questionnaire for Depression (PHQ-9) Godin-Shephard Leisure Time Physical Activity Scale (GSLTPAQ), and an index of the frequency to which patients engaged in goal-directed activities for living well (EUROIA). Methods ODYSSEE-vCHAT was a multi-centre, single group, open label study with assessments at baseline and end-of-study (approximately 11 months). Inclusion criteria were: ≥18 years of age, diagnosis of CHF (reduced ejection fraction (EF) ≤ 40%, mid-range EF, 41-49%, or preserved EF ≥ 50%); or CKD diagnosis (>10% risk for dialysis using the 4-variable, 2-year Kidney Failure Risk Equation, or on dialysis). Exclusion was based on inability to participate due to co-morbidities. The digital counselling protocol taught self-care skills to improve mental health, quality of life, and adherence to medications, exercise, diet, and smoke-free living (Figure 1). Patient engagement with ODYSSEE-vCHAT was defined as Not Engaged (0 logon minutes) vs. Engaged (> 0 logon minutes). The primary outcome was a minimal clinically important difference for MCS change: ΔMCS ≥ 3.8 or MCS ≥ 65 at baseline and study endpoint. It was assessed using multivariable binary logistic regression, controlling for exposure to COVID-19 and health literacy. Secondary outcomes were assessed using multivariable linear regression analyses with the same covariates. Results 215 patients were enrolled. There were 7 deaths and 34 withdrew. In our sample of 174 patients, mean age = 54.4 years (95% Confidence Interval, CI, 25, 81), gender identity as women, n = 68 (39%), ethno-racial group other than White, n = 83, (48%), primary diagnosis, CHF, n = 68 (39%), and CKD, n = 106 (61%). Duration of enrolment to end-of-study: median = 352 days, (95% CI, 159, 496). Engagement with ODYSSEE was associated with therapeutic change on the MCS (for both CHF and CKD patients, and CHF patients alone), GSLTPAQ, and EUROIA, but not the PHQ9 or ESSI (Figure 2). Conclusions Automated digital counselling with social network support promotes improvement in indices of mental health for patients with CHF and CKD. These findings support a follow-up randomized controlled trial.Figure 1.ODYSSEE-vCHAT Study ProtocolFiFigure 2.ODYSSEE-vCHAT Study Outcomes

Automated digital counselling with social network support for chronic heart failure fails to improve health status but promotes health-related quality of life: ODYSSEE-vCHAT pilot trial

Abstract Background Automated digital counselling programs have the potential to provide a scalable, complementary behavioural intervention to improve clinical outcomes for chronic heart failure (CHF). Purpose The primary hypothesis for this pilot trial was that automated digital counseling with social network support (ODYSSEE-vCHAT) vs. Usual Care would decrease the incidence of all-cause re-hospitalization or ED visits. Secondary outcomes included: minimal clinically important difference for improvement on the Kansas City Cardiomyopathy Questionnaire-Overall Summary (KCCQ-OS), and improvement on ENRICHD Social Support Index (ESSI), Patient Health Questionnaire for Depression (PHQ-9) Godin-Shephard Leisure Time Physical Activity Scale (GSLTPAQ), and Self-Efficacy in Managing Chronic Disease (SEMCD6). Methods This 2-arm, parallel group, single-blind pilot trial randomized patients to ODYSSEE-vCHAT vs. Usual Care. Patients were ≥18 years of age with CHF (reduced ejection fraction [HFrEF] < 40%, mid-range [HFmrEF] 40-49%, or preserved [HFpEF] ≥ 50%). Exclusion was based on inability to participate due to co-morbidities. All-cause hospitalization or ED visit were assessed digitally by hospital administrative data. Questionnaires were administered at baseline and end-of-study (approximately 8 months). The digital counselling protocol aimed to improve CHF self-care, HRQL, and adherence to medications, exercise, diet, and smoke-free living (Figure 1). The primary outcome was assessed using multivariable binary logistic regression. Secondary outcomes were assessed using multivariable linear regression analyses with ethno-racial group as a covariate. Results 61 patients were randomized: ODYSSEE-vCHAT, n = 30 (49%), vs. Usual Care, n = 31 (51%). There were 2 deaths, 3 withdrawals, and 12 patients failed to complete secondary outcome assessments. Sample characteristics included mean age = 59 years (95% Confidence Interval, CI, 30, 76), gender identity as women, n = 23 (38%), ethno-racial group other than White, n = 17, (28%) and CHF with HFrEF, n = 47 (77%), HFmrEF, n = 8 (13%), and HFpEF, n = 4 (7%). Duration of enrollment to trial endpoint: mean = 247 days, (95% CI, 75, 382). Figure 2 indicates that ODYSSEE-vCHAT was not associated with lower incidence of all-cause hospitalization/ED visit: composite index events for Usual Care, n = 8 (28%), ODYSSEE-vCHAT, n = 7 (23%). However, ODYSSEE-vCHAT was associated with greater prevalence of KCCQ-OS change (≥ 5 points), and greater improvement in self-efficacy (SEMCD6) for managing CHF. There was a statistical trend to decreased prevalence of depression. Social support was inversely associated with ODYSSEE-vCHAT. No benefit was observed for physical activity (Figure 2). Conclusions Automated digital counselling with social network support promotes improvement in HRQL indices, but not health status. Findings for this pilot trial support a follow-up phase 2 randomized controlled trial.Digital Counselling ProtocolODYSSEE-vCHAT Outcomes

Swinging Pendulum: The Social Adaptation of Returnees from Universities

College teachers now have more opportunities to engage in transnational education as people enter a new era of globalization and the shift toward a knowledge-based society. However, they also face various challenges in social adaptation. It has become a critical issue to enhance the sense of belonging and career resilience of the returnees from universities. By using a qualitative research method with the data from a respective provincial university in China, this study aims to explore the process and influencing factors of the social adaptation of returnees and finds that the social adaptation of returnees has gone through the process of longing, division, adjustment, and integration, which varies with individual and cultural differences. Social adaptation is similar to the swing and vibration of a clock. The working environment is the primary source of adverse cultural impact and ones social network support is negatively associated with social adaptation. Also, self-efficacy and informal social support networks play key roles in the adaptation process. To mitigate the re-entry shock, recommendations include optimizing work environments, providing emotional counseling, and enhancing organizational structures.

Displaying Altruism as a Sexual Signal in Human Mate Choice is an Adaptation – An Interdisciplinary Overview of the Evidence

AbstractNumerous studies in humans have shown that altruism may influence mate choice decisions, highlighting its potential role as a sexual signal. Whether using altruism as a signal is an adaptation, however, remains largely unresolved. In this review, we aim to investigate the adaptive nature of altruism as a sexual signal by constructing a comprehensive nomological network of evidence. Drawing upon interdisciplinary scientific modes of evidence (psychology, medicine, physiology, genetics, phylogenetics, hunter-gatherer studies, cross-cultural studies, and theoretical studies), our analysis reveals an extensive breadth of evidence across the various disciplines supporting the hypothesis that altruism is an adaptive sexual signal. However, only the psychological evidence demonstrates substantial depth. Other fields exhibit a lack of variation in research methods or a minimal amount of studies, limiting the strength of their respective contributions. Despite these limitations, there is still sufficient support for the nomological network. Based on the evidence of the various disciplines, we conclude that there is sufficient support that altruism as a sexual signal is an adaptation. We provide considerations for future research that would expand the scope of the evidentiary depth across the various disciplines, which would strengthen our understanding of the role of sexual selection in human altruism.

Research on New Spatial Data Infrastructure Supports the Circulation of Geographic Information Data Elements

Abstract. Data is an important factor of production in the digital economy era and an important support for building a new development pattern. As an important part of data resources, geographic information data is also an important new factor of production, which plays a unique role in the construction of digital China and economic and social development. From the perspective of releasing the value of data elements, data infrastructure is a new type of infrastructure that provides integrated data aggregation, processing,circulation, application, operation, and security services for society under the support of network, computing power and other facilities. It is an organic whole covering hardware, software, open source protocols, standards, and mechanism design. Spatial data infrastructure (SDI) is a collection of technologies, policies and systems that realize the access and access of spatial data. Through the construction of new spatial data infrastructure (NSDI), it supports the circulation of geographic information data elements,making it an important part of data infrastructure. Firstly, this paper gives the connotation of geographic information data elements circulation. Secondly, it proposed to construct the circulation system of geographic information data elements on the basis of enumerating and summarizing the spatial data infrastructure, in order to better support the construction of digital China and economic and social development. Thirdly, the basic requirements, technical indicators and overall architecture of NSDI are designed. Finally, the opportunities and challenges faced by the circulation of geographic information data elements were summarized, mainly focusing on the aspects of policy mechanisms and security systems. At the end of the paper is a summary and acknowledgments.

Decoding wheat contamination through self-assembled whole-cell biosensor combined with linear and non-linear machine learning algorithms

The contamination of mycotoxins is a serious problem around the world. It has detrimental effects on human beings and leads to tremendous economic loss. It is essential to develop a rapid and non-destructive method for contamination recognition particularly for early alarm. In this study, the whole-cell biosensor array was constructed and employed for rapid recognition of wheat contamination by combining with machine learning algorithms. Seven key VOCs were explored through univariate coupling to multivariate analysis of orthogonal partial least squares-discrimination analysis (OPLS-DA) models. The promoters of dnaK, katG, oxyR, soxS obtained from the stress-responsive of key VOCs were fused to the bacterial operon and fabricated on the whole-cell biosensor. The constructed whole-cell biosensor array was consisted with four kinds of sensors and 18 sensor unit. The bioluminescent intensity combined with linear machine learning algorithm of partial least squares discriminant analysis (PLS-DA) and non-linear algorithms of back propagating artificial neural network (BP-ANN) and least square support vector machine (LS-SVM) were employed to establish discrimination models for mold contamination especially for early warning. The Monte-Carlo strategy was performed to generate thirty subsets for modeling to give more reliable results. As a result, the whole-cell biosensor combined with non-linear algorithm of LS-SVM was practicable for detecting mold identification for wheat early-warning with the accuracy of 97.24%. Additionally, this study provides practical and effective methods not only for wheat quality guarantee and supervision but also for other foodstuffs.

MODEL PERCEIVED SOCIAL SUPPORT PEREMPUAN KADER SURABAYA HEBAT DALAM PENURUNAN PREVALENSI STUNTING

Stunting is a health problem in children due to chronic malnutrition that has a negative impact. Reducing the prevalence of stunting is a commitment of Kader Surabaya Hebat (KSH) women by prioritizing perceived social support. The role of KSH women as the leading sector in reducing the prevalence of stunting is evident in this study. This study aims to explore the model and process of perceived social support in the role of KSH women in the community. KSH women are also the main focus of the research and how the model becomes a modality of character building in Surabaya City. This research uses descriptive qualitative methods through observation and interviews. The results showed that the perceived social support model applied by KSH women is emotional support, instrumental support, information support, appreciation support, and social network support. The process of perceived social support starts from face-to-face dialogue, building trust, commitment to the process, sharing understanding, and temporary results that are carried out have gone well and are effective in reducing the prevalence of stunting in Surabaya City. Key words: KSH Women, Stunting, Perceived Social Support

Deep Learning-Enabled Dynamic Model for Nutrient Status Detection of Aquaponically Grown Plants

Developing models to assess the nutrient status of plants at various growth stages is challenging due to the dynamic nature of plant development. Hence, this study encoded spatiotemporal information of plants within a single time-series model to precisely assess the nutrient status of aquaponically cultivated lettuce. In particular, the long short-term memory (LSTM) and deep autoencoder (DAE) approaches were combined to classify aquaponically grown lettuce plants according to their nutrient status. The proposed approach was validated using extensive sequential hyperspectral reflectance measurements acquired from lettuce leaves at different growth stages across the growing season. A DAE was used to extract distinct features from each sequential spectral dataset time step. These features were used as input to an LSTM model to classify lettuce grown across a gradient of nutrient levels. The results demonstrated that the LSTM outperformed the convolutional neural network (CNN) and multi-class support vector machine (MCSVM) approaches. Also, features selected by the DAE showed better performance compared to features extracted using both genetic algorithms (GAs) and sequential forward selection (SFS). The hybridization of deep autoencoder and long short-term memory (DAE-LSTM) obtained the highest overall classification accuracy of 94%. The suggested methodology presents a pathway to automating the process of nutrient status diagnosis throughout the entire plant life cycle, with the LSTM technique poised to assume a pivotal role in forthcoming time-series analyses for precision agriculture.

Psychotherapy as a Determinant of Quality of Life among Older Persons

Purpose: This study delves into the experiences of elderly individuals undergoing psychotherapy, evaluating its effects on their quality of life and well-being, and identifying unique challenges and benefits in later life. Theoretical reference: The resilience theory, as explored in this study, highlights a multi-dimensional nature encompassing health, psychology, and social work, emphasizing the importance of examining adversity and outcomes and advocating for interdisciplinary approaches to understand and operationalise resilience across individuals, organizations, and communities. Method: A qualitative approach was utilized to gather deep insights into ten (10) participants’ experiences and the subjective impact of psychotherapy on their lives, highlighting the role of specific interventions in promoting psychological well-being. Results and Conclusion: Findings indicate that psychotherapy significantly enhances older individuals' psychological health, fostering positive self-evaluation, growth, meaningfulness, quality relationships, effective life management, and autonomy. The study further identifies critical challenges in accessing psychotherapy, such as financial, transportation, and mobility barriers. Implications of research: The research emphasizes the necessity for psychotherapeutic interventions that include family and social network support to positively influence older adults' well-being, addressing the identified access challenges. Originality/value: This study contributes unique insights into the psychotherapeutic experiences of the elderly, highlighting its crucial role in enhancing quality of life and addressing specific life stage challenges, thus adding valuable knowledge to geriatric psychotherapy literature.

Physics-informed neural networks in support of modal wavenumber estimation.

A physics-informed neural network (PINN) enables the estimation of horizontal modal wavenumbers using ocean pressure data measured at multiple ranges. Mode representations for the ocean acoustic pressure field are derived from the Hankel transform relationship between the depth-dependent Green's function in the horizontal wavenumber domain and the field in the range domain. We obtain wavenumbers by transforming the range samples to the wavenumber domain, and maintaining range coherence of the data is crucial for accurate wavenumber estimation. In the ocean environment, the sensitivity of phase variations in range often leads to degradation in range coherence. To address this, we propose using OceanPINN [Yoon, Park, Gerstoft, and Seong, J. Acoust. Soc. Am. 155(3), 2037-2049 (2024)] to manage spatially non-coherent data. OceanPINN is trained using the magnitude of the data and predicts phase-refined data. Modal wavenumber estimation methods are then applied to this refined data, where the enhanced range coherence results in improved accuracy. Additionally, sparse Bayesian learning, with its high-resolution capability, further improves the modal wavenumber estimation. The effectiveness of the proposed approach is validated through its application to both simulated and SWellEx-96 experimental data.

Examining support marshalling within an asynchronous online peer support forum for individuals affected by dementia.

Online support communities may provide individuals affected by dementia opportunities for reciprocal peer support, however, the support marshalling strategies employed and their success remain unclear. Analysis of 100 randomly selected conversation threads from the Dementia Support Forum indicated that 29% (29/100) of opening posts included a direct support marshalling strategy (i.e. explicit support request) compared with 54% (54/100) labelled as indirect, with the remainder not seeking support. Within the direct marshalling posts, informational support was the most frequently requested (n = 23), followed by network support (n = 7), emotional support (n = 5) and esteem support (n = 1) with analysis of subsequent posts confirming that the types of support requested were present within responses. Regardless of whether a direct or indirect strategy was used, most posts received a response, typically on the same day. Other response facets were comparable, apart from thread duration with conversations elicited through a direct strategy being longer (M = 39.71 vs 14.62 days).

Searching for Love and Babies: A Qualitative Study on Online Social Support Among Women with Infertility

ABSTRACT With the popularity of computer-mediated communication, accessing online social support has become more accessible for women confronting infertility, yet the role of such support for Chinese women remains understudied. This study investigates the online social support experiences of Chinese women navigating infertility within the framework of Cutrona and Suhr’s social support. Employing netnography and semi-structured interviews alongside thematic analysis, the findings highlight challenges in informational support due to limitations in online information dissemination, with some degree of overlap observed between informational support and network support. Emotional support proves crucial and esteem support aids in mitigating self-blame among online forum members. Tangible assistance primarily involves expressed willingness to help. This research advances social support theory by exploring new areas, clarifying online support mechanisms using Daena Goldsmith’s normative approach, highlighting sociocultural influences, and enhancing understanding of esteem support in the context of stigmatization.

Roles of financial literacy and entrepreneurial orientation in economic empowerment of rural women entrepreneurs

ABSTRACT Policy makers, particularly in developing countries, view entrepreneurship as a stepping stone for achieving women’s economic empowerment. However, simply attaching women to the labour market and providing them access to financial resources may not transform their economic well-being unless it is accompanied by agencies such as financial literacy and entrepreneurial orientation. In this context, we empirically test the seminal theoretical framework of Kabeer (1999) for understanding women empowerment, using primary data for 820 Indian rural women entrepreneurs. Employing alternate empirical specifications and using instrumental variable regression to address the potential endogeneity of financial literacy, we find that financial literacy and entrepreneurial orientation play important roles in enhancing financial well-being, our measure of economic empowerment. The results hold even after controlling for the experience of the entrepreneur, family support and strength of social network. The findings call for designing interventions to foster financial literacy among poor women entrepreneurs.

The Role of NGOS in Promoting Women Entrepreneurship in India

In recent times, the government has realized the importance of entrepreneurship as a prominent alternative to traditional wage employment in the new economy, and its role in increasing the pace of economic growth. Therefore, Indian government has come up with various special policy measures to help women entrepreneurs. there are major limitations among women entrepreneurs in accessing those facilities. These limitations arise due to various factors, such as: lack of awareness, lack of information, difficulty in accessibility of finance, lack of easy access of entrepreneurial training and post training support, lack of market and network support, lack of self-confidence and managerial skills, bureaucratic hassles, lack of transportation mainly in remote areas, restriction of government officials in terms of timing when women also have to perform household activities etc.

Resource allocation in RISs-assisted UAV-enabled MEC network with computation capacity improvement

Unmanned aerial vehicle (UAV)-enabled mobile edge computing (MEC) networks have recently been considered to be a support for ground MEC networks to enhance their computation capability. However, the line-of-sight (LOS) channels between the UAV and Internet of Things (IoT) devices can be interfered by various obstacles, such as trees and buildings, resulting in a considerable reduction in the capacity of MEC networks. To solve this issue, a system that combines multiple reconfigurable intelligence surfaces (RISs) with a UAV-enabled MEC network is proposed in this study. A UAV equipped with edge servers is treated as an aerial computing platform for IoT devices, and multi-RISs are utilized to simultaneously improve the communication quality between enhanced UAV and IoT devices. To maximize the sum computation bits of the system, a problem that jointly optimizes the time slot partition, local computation frequency, transmit power of the devices, UAV receive beamforming vectors, phase shifts of the RISs, and the trajectory of the UAV is formulated. The problem is a typical nonconvex optimization problem; therefore, we propose a recursive algorithm based on the successive convex approximation (SCA) and block coordinate descent (BCD) technology to find an approximate optimal solution. Simulation results demonstrate the effectiveness of the proposed algorithm compared with various benchmark schemes.

Association of support group leader experience with Scleroderma Patient-centered Intervention Network Support group Leader EDucation Program outcomes: Secondary analysis of a two-arm parallel partially nested randomized controlled trial

Introduction/Objective: The Scleroderma Patient-centered Intervention Network Support group Leader EDucation Program was found in a randomized controlled trial to substantially improve leader self-efficacy. Whether the program is effective for leaders with different levels of experience, including candidate leaders with no prior experience and leaders with ⩽3 years experience or ⩾4 years experience, is not known. The objective of the present post hoc secondary analysis was to evaluate outcomes by leader experience, age, and education. Methods: The trial was a pragmatic, two-arm partially nested randomized controlled trial with 1:1 allocation to intervention or waitlist control. Eligible participants were existing or candidate support group leaders. The 13-session leader training was delivered in groups of five to six participants weekly via videoconference in 60- to 90-min sessions. The primary outcome was leader self-efficacy, measured by the Support Group Leader Self-efficacy Scale (SGLSS) immediately post-intervention. Secondary outcomes were Support Group Leader Self-efficacy Scale scores 3 months post-intervention and emotional distress, leader burnout, and volunteer satisfaction post-intervention and 3 months post-intervention. Leaders were classified as having no experience, ⩽3 years experience, or ⩾4 years experience. Results: A total of 148 participants were randomized to intervention (N = 74) or waitlist (N = 74). Compared to leaders with ⩾4 years of experience, Support Group Leader Self-efficacy Scale scores were non-statistically significantly higher post-intervention for leaders with 0–3 years experience and lower for leaders with no experience. The 3 months post-intervention Support Group Leader Self-efficacy Scale scores were significantly lower for leaders without experience and similar for leaders with 0–3 years to those with ⩾4 years experience. There were no differences by experience on other outcomes or by age and education on any outcomes. Conclusion: Support group leader education improved leader self-efficacy but was most effective for leaders with experience prior to initiating the program. Trial Registration: NCT03965780; registered on May 29, 2019.

Do Non-Clinical Services Help to Improve Functional Outcomes Among Young Adults With Mental Disorders? A Systematic Review.

Mental disorders during young adulthood can significantly impair functioning in daily activities. Non-clinical support services aim to improve functioning by helping people to build social and life skills, participate in education and employment and improve physical health. This study aims to examine and synthesise the evidence for non-clinical services on improving functional outcomes for young adults with mental disorders. A systematic search was undertaken to identify quantitative and qualitative studies reporting on a non-clinical service component (vocational support, peer support, youth development, lifestyle interventions, family and network support) and examining functional outcomes (e.g., outcomes focussed on work and education, life skills, relationships and healthy behaviours). Seventeen studies met inclusion criteria. Identified studies focussed on vocational support services (n = 9), lifestyle interventions (n = 6) and family and network support services (n = 2). No studies on peer-support services or youth development services were found. More than half of the vocational support service studies reported increased employment rates among young adults (n = 6). Studies focussing on lifestyle interventions included a combination of physical activity, nutrition education, health coaching and motivation and behaviour change. However, the measures of functioning used across studies were too varied to determine whether lifestyle interventions may be useful in improving functional outcomes for young adults. Further research is needed to understand the impact of non-clinical services on functioning. This evidence will provide pragmatic guidance for service planners to invest in supports and interventions that make a meaningful difference to the lives of young adults living with mental disorders.

Deep neural network-enabled multifunctional switchable terahertz metamaterial devices

Under the support of deep neural networks (DNN), a multifunctional switchable terahertz metamaterial (THz MMs) device is designed and optimized. This device not only achieves ideal ultra-wideband (UWB) absorption in the THz frequency range but enables dual-functional polarization transformation over UWB. When vanadium dioxide (VO2) is in the metallic state, the device as a UWB absorber with an absorption rate exceeding 90% in the 2.43–10 THz range, with a relative bandwidth (RBW) of 145.2%, and its wideband absorption performance is insensitive to polarization. When VO2 is in the insulating state, the device can switch to a polarization converter, achieving conversions from linear to cross polarization and from linear to circular polarization in the ranges of 4.58–10 THz and 4.16–4.43 THz, respectively. Within the 4.58–10 THz range, the polarization conversion ratio approaches 100% with an RBW of 74.3%, the polarization rotation angle is near 90°. Within the 4.16–4.43 THz range, the RBW is 6.29% and the ellipticity ratio approaches 1, Moreover, the effects of incident angle and polarization angle on the operational characteristics are studied. This THz MMs due to its advantages of wide angle, broad bandwidth, and high efficiency, provides valuable references for the research of new multifunctional THz devices. It has great application potential in short-range wireless THz communication, ultrafast optical switches, high-temperature resistant switches, transient spectroscopy, and optical polarization control devices.

Reciprocity and patron-clientelism as forms of an institution of mutual assistance network in villages of the Republic of Tatarstan

The sustainability of the rural world of the Republic of Tatarstan today largely depends on the development and functioning of the institution of network mutual assistance. I attempt to study the situation, making use of network theories in sociology as well as concepts of reciprocal and patron-client relationships as key aspects in the reproduction of mutual assistance networks. Drawing on field interviews collected in various villages of Tatarstan, I examine the actors and practices of mutual assistance in reciprocal and patron-client rural relationships and argue for the necessity of further support and development of mutual assistance networks in rural areas as a way of securing collective mutual insurance in an unstable economic situation.

Regulating the closed pore structure of biomass-derived hard carbons towards enhanced sodium storage

Hard carbon (HC) stands out as a promising anode material for sodium storage due to its unique structure. However, the pore structure regulation of HC still poses a significant challenge. Herein, we propose a combined method of hydrothermal pretreatment, freeze-drying, and high-temperature carbonization to regulate the pore structure of HC. During the hydrothermal processes, the assembly of graphene oxide (GO) with starch facilitates the formation of open pores, which are subsequently transformed into closed pores during high-temperature carbonization. Impressively, a hard carbon with a reversible capacity of 434 mA h g −1 at 30 mA g −1 has been prepared through the structure regulation. Compared to the sample without structural regulation, it demonstrates a remarkable increase of 184.21 mA h g−1, with an enhancement rate of 73.80 %. Simultaneously, the skeletal structure of GO serves as a conductive network and framework support, enabling favorable rate performance and excellent cycling stability. Furthermore, the sodium storage mechanism is deduced as “adsorption -- intercalation -- pore filling”. Overall, this study can offer valuable insights into pore structure regulation for anode materials and shed light on sodium storage mechanisms.