Weak Capability Research Articles

FL-YOLOv7: A Lightweight Small Object Detection Algorithm in Forest Fire Detection

Given the limited computing capabilities of UAV terminal equipment, there is a challenge in balancing the accuracy and computational cost when deploying the target detection model for forest fire detection on the UAV. Additionally, the fire targets photographed by the UAV are small and prone to misdetection and omission during detection. This paper proposes a lightweight, small target detection model, FL-YOLOv7, based on YOLOv7. First, we designed a light module, C3GhostV2, to replace the feature extraction module in YOLOv7. Simultaneously, we used the Ghost module to replace some of the standard convolution layers in the backbone network, accelerating inference speed and reducing model parameters. Secondly, we introduced the Parameter-Free Attention (SimAm) attention mechanism to highlight the features of smoke and fire targets and suppress background interference, improving the model’s representation and generalization performance without increasing network parameters. Finally, we incorporated the Adaptive Spatial Feature Fusion (ASFF) module to address the model’s weak small target detection capability and use the loss function with dynamically adjustable sample weights (WIoU) to weaken the impact of low-quality or complex samples and improve the model’s overall performance. Experimental results show that FL-YOLOv7 reduces the parameter count by 27% compared to the YOLOv7 model while improving 2.9% mAP50small and 24.4 frames per second in FPS, demonstrating the effectiveness and superiority of our model in small target detection, as well as its real-time and reliability in forest fire scenarios.

Ultrathin Space-Shift Phase-Coherent Cancellation Metasurface for Broadband Sound Absorption.

A space-shift phase-coherent cancellation acoustic metasurface is developed, which can achieve broadband low-frequency sound absorption via ultra-thin integrated structure composed of multiple units with weak absorption capability. Through a space-shift design of the channel length, the large-size required in the thickness direction for low-frequency absorption is transferred into an extremely ultra-thin space layer. The units with gradient channel length are compactly arranged in an ultra-thin layer through space folding, a coplanar sound absorption metasurface component with working bandwidth exceeding an octave and thickness of only λ/25 to λ/57 is obtained. As the construction of a special double-hole "bridge" layout, even if the elements are sparsely distributed, strong coupling interactions between the units can sustain. When a certain local phase relationship is satisfied, the coherent cancellation of sound energy can be achieved, so as to reduce the sound reflection and scattering, and enhance the absorption performance. Therefore, from the perspective of phase relationship among units, the present work provides more clear physical image and intuitive theoretical explanation for achieving excellent broadband sound absorption through parallel superposition of multiple units with weak absorption capability. The proposed ultra-thin sound absorbing metasurface can satisfy the thickness limitations and absorption performance requirements in most equipment.

Risk prediction of enterprise human resource management based on deep learning

BACKGROUND: The efficiency and accuracy of risk prediction in traditional enterprise human resource management (HRM) cannot meet practical needs. In response to this deficiency, this study proposes an enterprise HRM risk intelligent prediction model based on deep learning. METHODS: Two tasks were completed in this study. First, based on the existing research results and the current status of enterprise HRM, the HRM risk assessment system is constructed and streamlined. Second, for the defects of Back Propagation Neural Network (BPNN) model, Seagull Optimization Algorithm (SOA) is used to optimize it. The Whale Optimization Algorithm (WOA) is introduced to promote the SOA for its weak global search capability and its tendency to converge prematurely. RESULTS: By simplifying the HR risk assessment system and optimizing the BPNN using the SOA algorithm, an intelligent HRM risk prediction model based on the ISOA-BPNN was constructed. The results show that the error value of the ISOA-BPNN model is 0.02, the loss value is 0.50, the F1 value is 95.7%, the recall value is 94.9%, the MSE value is 0.31, the MAE value is 8.4, and the accuracy is 99.53%, both of which are superior to the other two models. CONCLUSIONS: In summary, the study of the HRM risk intelligent prediction model constructed based on ISOA-BPNN has high accuracy and efficiency, which can effectively achieve HRM risk intelligent prediction and has positive significance for enterprise development.

Space Communication Network in the New Era: Architecture, Key Technologies, and Challenges

Space communication network (SCN) is a feasible and flexible solution to enable global seamless coverage, as well as service orchestration in a wide range. It's emerged as a promising perspective for the next-generation communication network. However, the design of SCN architecture with both efficiency and security remains an open challenge. In this paper, we propose a new system architecture for SCN, along with new hardware components, such as the collaborative edge gateway, the reconfigurable label-based switch, etc. Meanwhile, three core capabilities of the proposed architecture are elaborated, including structural collaborative security, efficient adaptive communication, and distributed service orchestration. Firstly, as for single node of SCN has weak security capability, the structural collaborative security aims to establish a strengthened security structure among nodes. Through security associations and strategy collaborations, nodes in the structure can cooperate to resist large-scale distributed attacks. Secondly, instead of fixed coverage and limited protocol exchange, the efficient adaptive communication introduces communication resource adaptation to realize on-demand resource scheduling, and introduces transmission protocol adaptation to support more heterogeneous connections. Thirdly, to solve the efficiency problem of centralized orchestration in a wide area, a smart agent with a learning-based Pattern-Matching Library is constructed, namely, a distributed component to execute near real-time service orchestration, which uses decomposing-based orchestration optimization to accomplish a lower service latency. In addition to the key technologies, some future research directions are also provided for enlightening the researchers.

Research on the Impact and Optimization of Industrial Structure Adjustment on Marketing Strategy of Financial Institutions in the Digital Economy Era

The role of marketing strategy in the industrial structure adjustment and development of financial institutions in the era of the digital economy has changed marketing strategy and made the industrial structure adjustment of financial institutions in the era of the digital economy a hot spot. However, in the process of changing the marketing strategy of financial institutions, there are problems such as poor marketing concepts, weak online sales capabilities, network data analysis, and small mining volume. The main reason is that the traditional marketing model does not use information management technology to restrict the development of financial institutions. Therefore, this paper proposes a marketing method based on information management technology to plan the marketing strategies of financial institutions with different networks. First, phyton software is used to collect financial institutions' marketing data from the Guoan Tai database in 2018~2022, and according to the collected data of 33 financial institutions for analysis. Then, the judgment of marketing strategy is based on information management technology to improve the accuracy of financial institutions' selection of marketing strategy. The adjustment results show that under the background of the digital economy, information technology can improve the marketing strategy selection of financial institutions, promote the optimization of marketing strategies of financial institutions, and respond to the requirements of the financial market. Information technology can improve the accuracy and effect of marketing strategy selection of financial institutions, making its accuracy greater than 90%, which is significantly better than 80% of the manual identification method. At the same time, information technology can improve the recognition rate of marketing strategy, which is more than 80%, and provide support for the formulation of marketing strategy. Therefore, under the condition of a digital economy, industrial structure has a significant impact on the marketing strategy of financial institutions, while information technology methods can identify strategic indicators, improve the effect and accuracy of strategy formulation, and promote the development of financial institutions.

Enhanced spinal cord regeneration by gelatin/alginate hydrogel scaffolds containing human endometrial stem cells and curcumin-loaded PLGA nanoparticles in rat

Spinal cord injury (SCI) is a serious problem with a high prevalence worldwide. The weak capability of the spinal cord for regeneration in association with upregulation of inflammatory factors is two key obstacles against a full SCI repair. Curcumin is a natural substance with anti-inflammatory and neuroprotective effects. Here, we have used a combined strategy using stem cells and hybrid hydrogel scaffolds loaded with curcumin for SCI repair. Curcumin-loaded PLGA nanoparticles were prepared, characterized, and encapsulated into gelatin/alginate hydrogel scaffolds, which were then seeded by human endometrial stem cells (hEnSCs). The resulting construct was studied using in vitro and in vivo experiments on rat models. DLS, SEM, Zeta potential, and FTIR data confirmed the successful addition of curcumin to PLGA nanoparticles. SEM analyses indicated the successful addition of curcumin-loaded nanoparticles into the gelatin/alginate scaffold, as well as the adherence of the seeded EnSCs. Based on the results, the prepared constructs not only allowed the controlled release of curcumin but also could support the survival and growth of hEnSCs. Based on the results of BBB and histological experiments, the highest BBB score was related to the combined strategy, consistent with histological outcomes, in which our hEnSC-seeded gelatin/alginate scaffold containing curcumin-loaded nanoparticles led to improved structures of the white and gray matters in the SCI site, being indicative of the superior nerve fiber regeneration, compared to other studied groups. These results indicate the efficiency of the proposed method for SCI repair and broaden the scope for subsequent studies on spinal cord regeneration.

Oligomerization Strategy of D-A-Type Conjugated Molecules for Improved NIR-II Fluorescence Imaging.

Fluorescence imaging (FI) in the second near-infrared (NIR-II) window has emerged as a promising imaging method for cancer diagnosis because of its superior properties such as deep penetration depth and high signal-to-background ratio. Despite the superiorities of organic conjugated nanomaterials for NIR-II FI, the issues of low fluorescence quantum yield, weak metabolic capability, undefined molecular structure for conjugated polymers, weak light-harvesting ability, short emission wavelength, and high synthetic complexity for conjugated small molecules still remain to be concerned. We herein propose an oligomerization strategy by facilely adjusting the oligomerization time to balance the advantages and disadvantages between conjugated polymers and small molecules, obtaining the candidate (CO1, oligomerization time: 1 min) with the optimal NIR-II optical performance. Then the CO1 is further prepared into water-dispersed nanoparticles (CON1) via a nanoprecipitation approach. By virtue of the suitable size, excellent NIR-II optical properties, low toxicity, and strong cell-labeling ability, the CON1 is successfully employed for in vivo NIR-II imaging, permitting the real-time visualization of blood vascular system and tumors with high sensitivity and resolution. This work thus not only provides a personalized organic conjugated nano-agent for NIR-II FI, but also highlights the molecular strategy for the development of organic conjugated systems with optimal performance for bio-imaging.

Identifying Human Capital Readiness and Digital Culture toward Employee Performance in Facing Industry 4.0: Case of Pt Perusahaan Listrik Negara Province X

The emergence of Industry 4.0 has brought changes and challenges to PT Perusahaan Listrik Negara (PLN). In order to adapt and thrive in this new era, it is crucial for companies to identify and enhance their human capital readiness and digital culture toward employee performance. The performance of employees generally has the potential to enhance the productivity of a company in achieving its goals. However, in the process of transforming and improving employee performance in the era of Industry 4.0, PT Perusahaan Listrik Negara (PLN) faces important challenges, namely the lack of mature employee readiness and weak digital capabilities. This study aims to identify the impact of human capital readiness and digital culture on employee performance in the context of facing Industry 4.0. Industry 4.0 represents a significant transformation in the way businesses operate, driven by advancements in digital technology and automation. The study focuses on understanding how the readiness of employees in terms of skills, knowledge, and attitudes, as well as the organizational culture surrounding digital adoption, influence employee performance in the era of Industry 4.0. The research found will be used to determine which dimensions need to be prioritized in order to enhance the “Amount of Work,” “Punctuality,” and “Quality of Work,” aiming to address the company’s shortcomings in both work processes and systems. Based on the analysis, it is found that Soft Skills, Attitude, Digital First Mindset, Flexibility and Agile, and Data Driven Decision Making are the dimensions with the highest priority. These indicators are crucial factors that require improvement. Based on the research found, the proposed programs as company strategies to improve employee performance include enhancing employee capabilities through seminars and workshops related to digital technology. Additionally, improving the company’s technology is essential to enable employees to operate and apply their work digitally.

Robust adaptive enhancement algorithm for multi-modal high grayscale image displaying on low-bit monitors based on HIS and priori knowledge

Gray-scale images are widely used in many fields, including satellite remote sensing, autonomous driving, medical CT, and X-ray detection, but gray-scale images have many shortcomings, such as high bit, low contrast, and high dynamic ranges. The visual analysis of these images is complicated and limited by people's psychology and physiology, and pseudo-color technology is an effective way to solve this problem. To address the weak adaptive capability, poor robustness, and insufficient generalization of existing pseudo-color enhancement methods, an adaptive enhancement algorithm for high grayscale images based on prior knowledge and HIS space, called APKHHIS, was proposed. Firstly, an adaptive gray-scale image correction mapping algorithm based on original prior knowledge was designed, and the quantization of images with different bit depths is realized. Secondly, to ensure the effectiveness of the enhanced data, an adaptive power compensation method was designed to compensate for the brightness of the gray-scale corrected images. Finally, an adaptive brightness and power correction algorithm was innovatively designed for the first time, which can adaptively adjust the color saturation and spatial brightness of the image more reasonably. To verify the effectiveness of the algorithm proposed in this paper, adaptive enhancement experiments were carried out on multi-modal data sets. The subjective and objective experimental results show that the APKHHIS algorithm can achieve the best performance on various data sets, and has strong robustness and universality, which provides an effective solution for the adaptive enhancement of multi-modal low-quality images.

Does managerial training increase SME managers' effectiveness? A capability development approach

PurposeTraining remains an important factor in developing the managerial effectiveness and capability of small and medium-sized enterprises (SMEs), yet there are concerns regarding the quality of training provided to SME managers in Ghana, hence the weak managerial capabilities observed in SME management. This study, therefore, examines the impact of managerial training on the effectiveness of SME managers in Ghana.Design/methodology/approachDrawing on the human capital theory (Becker, 1962; Rosen, 1977), this study employs the variance-based estimating technique, partial least square structural equation modelling (PLS-SEM) in estimating the effects of training on the managerial effectiveness of SME managers. Adopting a stratified random sampling technique, the study uses primary data collected from 506 SMEs in Ghana to test 4 hypothesised paths.FindingsFirst, the model result indicates that training accessibility and training content are statistically significant in explaining managerial effectiveness at a 1% level. However, both training efficiency and training frequency are statistically insignificant in explaining managerial effectiveness in Ghana. Second, while the industry category is found to influence the relationship between training and managerial effectiveness, gender, manager's age and education are insignificant in explaining any effects.Research limitations/implicationsThough the sample size is large, the findings from this study could not be generalised to the whole of Ghana since it is regionally based. The study could benefit immensely from a triangulated method where a qualitative dimension could provide deeper insight into some of the findings in this study.Originality/valueStudies of this nature focussing on the managerial effectiveness of SME managers in the Ghanaian context is rare. This is one of the few studies in the Ghanaian research context which focuses on the capability development approach in the delivery of managerial training to SMEs.

Financial literacy, network competency, market orientation and financial performance: A study from Bandung SMEs

Indonesia SMEs have contributed 61.97% to GDP or Rp. 8,573.89 trillion, and they can absorb almost 97% of the workforce. However, several problems arise and become limitations for SMEs, such as limited capital and limited marketing ability and weak business management capabilities. For capital limitations, it can be solved by applying for credit to external parties such as banks and venture capital, but SMEs must meet the bank requirements. For marketing limitations, it can be pursued by maximizing the ability of SMES actors in network competence and market orientation. Therefore, this research was conducted to examine the financial literacy, network competence, and market orientation to the financial performance of SMEs. We collected data by an online questionnaire on 197 SMEs in Bandung. We use SEM PLS to analyze the data. Our results indicated that financial literacy, network competence, and market orientation had a positive and significant impact on the SMEs financial performance. That means that the ability to understand financial concepts, the ability to establish good relationships or networks with external parties, and the ability to sense markets and customer relations help SMEs to implement their business strategies properly. So that they will have an impact on increasing financial performance.

Enhanced degradation of methylene blue dye using flexible SiO2–TiO2 nanofiber membranes

Titanium dioxide (TiO2) is widely regarded as one of the most extensively applied photocatalytic semiconductor materials. However, conventional powdered titanium dioxide exhibits certain limitations, including relatively weak light absorption capability, a small surface area and insufficient active sites. This study successfully prepared flexible and porous silicon dioxide (SiO2)–titanium dioxide nanofiber membranes (NFMs) by implementing electrospinning technology and calcination processes. The porous membranes demonstrate remarkable performance in water treatment, featuring a high specific surface area (49 m2/g) and porosity, enabling efficient adsorption and removal of organic pollutants in water. Remarkably, the NFMs-800 variant exhibits outstanding photocatalytic performance, achieving complete removal of adsorbed organic compounds under ultraviolet irradiation. The design and fabrication methods of this porous membrane are simple and scalable, providing a potential solution for practical water-treatment applications. Consequently, the silicon dioxide–titanium dioxide porous membrane holds significant prospects in the field of water treatment, offering a promising contribution to the attainment of efficient and sustainable water resource management.

Local Rigidity by Flexibility: Unusual Design for Organic THz‐Device Materials

AbstractTerahertz (THz) waves interact with molecular phonon vibrations of organic matter. When designing organic THz‐device materials, conformational flexible groups (CFGs) are in most cases avoided. CFGs create many low‐energy conformers with high conformational entropy, which results in large and many phonon vibration modes that lead to undesired self‐absorption of THz waves. Here, nonpolar CFGs only having weak intermolecular interaction capability are unusually introduced into organic THz‐device materials, utilized for efficient THz wave generation. Newly designed THz‐source crystals possess nonpolar methylene (CH2)n units having high conformational flexibility. Compared to previously reported benchmark crystals without methylene CFGs, introducing methylene CFGs significantly reduces void volume in newly designed crystals. This leads to the suppression of molecular phonon vibrations below 2.0 THz (i.e., introducing flexibility results in local rigidity). At infrared pump wavelengths, new CFG‐contained crystals generate a strong THz electric field that is one order of magnitude stronger than that generated in inorganic ZnTe crystals. CFG‐contained crystals exhibit a flatter spectral shape of the generated THz wave than benchmark crystals without methylene CFGs. Therefore, the introduction of CFGs is a very intriguing design strategy for organic THz‐device materials to reduce the limitations caused by phonon vibrations.

MoS2 nanosheets supported on anodic aluminum oxide membrane: An effective interface for label-free electrochemical detection of microRNA

The interesting adsorption affinity of two-dimensional nanosheets to single stranded over double stranded nucleic acids have stimulated the exploration of these materials in biosensing. Herein, MoS2 nanosheets decorated anodic aluminum oxide (AAO) membrane was simply prepared by suction filtration. The MoS2/AAO hybrid membrane was initially applied to the electrochemical detection of microRNA using let-7a as the model. When let-7a was incubated with its complementary DNA, double stranded DNA-RNA formed and which displayed weak adsorption capability to the hybrid membrane. And thus the steric effect combining the electrostatic repulsion of the backbone phosphate of nucleic acids for [Fe(CN)6]3− transport across the hybrid membrane varied with the concentration of let-7a. In this way, a label-free electrochemical detection method for microRNA was established by monitoring the change of the redox current of [Fe(CN)6]3−. To further improve the detection sensitivity of the method, we proposed two separate strategies focusing on the amplification of the target-induced steric hindrance with DNA nanostructure and the magnification of the electrode sensitivity for [Fe(CN)6]3− by electrode modification. By using the two strategies, the hybrid membrane based-detection method exhibited broad linear range, low detection limit and good selectivity as well as reproducibility. Therefore, this study provided a proof-of-concept for the application of two-dimensional material to nucleic acids detection.

Dap-FL: Federated Learning Flourishes by Adaptive Tuning and Secure Aggregation

Federated learning (FL), an attractive and promising distributed machine learning paradigm, has sparked extensive interest in exploiting tremendous data stored on ubiquitous mobile devices. However, conventional FL suffers severely from resource heterogeneity, as clients with weak computational and communication capabilities may be unable to complete local training using the same local training hyper-parameters. In this paper, we propose Dap-FL, a deep deterministic policy gradient (DDPG)-assisted adaptive FL system, in which local learning rates and local training epochs are adaptively adjusted by all resource-heterogeneous clients through locally deployed DDPG-assisted adaptive hyper-parameter selection schemes. Particularly, the rationality of the proposed hyper-parameter selection scheme is confirmed through rigorous mathematical proof. Besides, due to the thoughtlessness of security consideration of adaptive FL systems in previous studies, we introduce the Paillier cryptosystem to aggregate local models in a secure and privacy-preserving manner. Rigorous analyses show that the proposed Dap-FL system could protect clients' private local models against chosen-plaintext attacks and chosen-message attacks in a widely used honest-but-curious participants and active adversaries security model. More importantly, through ingenious and extensive experiments, the proposed Dap-FL achieves higher model prediction accuracy than two state-of-the-art RL-assisted FL methods, i.e., 6.03% higher than DDPG-based FL and 7.85% higher than DQN-based FL. In addition, experimental results also show that the proposed Dap-FL achieves higher global model prediction accuracy and faster convergence rates than conventional FL, and the comprehensiveness of the adjusted local training hyper-parameters is validated.

Boosting fast electrode reaction kinetics of silicon suboxide anodes by fluoroethylene carbonate-based electrolyte

The growing demand for electric vehicles has led to an urgent need for higher-energy-density batteries. Silicon (Si) has been regarded as an alternative to graphite as an anode material owing to its high theoretical capacity. Nevertheless, the large volume change in Si during repeated charge/discharge causes serious particle fracture, leading to rapid capacity degradation. Silicon suboxide (SiOx) anodes show better cycling performance than Si because of their alleviated volume variation, yet still have unsatisfactory electrode reaction kinetics. Herein, fluoroethylene carbonate (FEC)-based electrolyte is proposed to enhance the electrochemical properties of SiOx anodes. A higher specific capacity of ∼1500 mAh g−1 at 0.5 A g−1 and an excellent rate capability of ∼1050 mAh g−1 at 4 A g−1 are obtained for the SiOx anode, which ensures an 83.5% capacity retention of SiOx||LiFePO4 cells after 300 cycles. The theoretical calculations and experimental studies reveal that FEC forms a weakly solvating electrolyte, enabling easier Li-ion desolvation and fast electrode reaction kinetics. Moreover, FEC reinforces the Li+-anion coordination owing to its weak solvating capability, thus a LiF-rich electrode/electrolyte interphase is formed through the co-decomposition of FEC and PF6− anions, leading to a tough SEI film formation with rapid ionic conductivity and good mechanical property.

Decent work, capabilities and flourishing at work

PurposeThis study aims to investigate the associations among decent work (DW), capabilities and the flourishing of employees in a South African context.Design/methodology/approachA cross-sectional survey was conducted with a convenience sample (N = 436) of early childhood development practitioners from two South African provinces. A demographic questionnaire, the Decent Work Scale, the Capability Set for Work Questionnaire and the Flourishing-at-Work Scale were administered.FindingsLatent class analysis showed four capability sets: robust, relational, knowledge/skills and weak capability sets. Employees with a robust capability set were more inclined to report DW than those with knowledge/skills and weak capability sets. Employees with a weak capability set were significantly less inclined to report organisational values that complement family and social values than the other three capability sets. Employees with a robust capability set reported significantly higher emotional well-being (EWB), psychological well-being (PWB) and social well-being (SWB) levels than those with relational, knowledge/skills and weak capability sets. DW was significantly related to EWB, PWB and SWB.Originality/valueThis study contributes to the literature regarding DW, capabilities and flourishing of employees in a non-western, educated, industrialized, rich and democratic and non-POSH context. The study highlights the need for well-being policies that focus on DW and the capabilities of people in disadvantaged positions. These together would strengthen their agency for converting capabilities into well-being.

Fowler-Nordheim tunneling mechanism Graphene/GaN ultraviolet position-sensitive detector with high precision for optoelectronic demodulation applications

As an important component of optical sensors, position-sensitive detector (PSD) plays an important role in non-contact measurement systems and is widely used in many important fields. However, the preparation and application of ultraviolet (UV) PSD are still to be studied. Herein, we propose a high precision UV PSD constructed by graphene (Gr)/GaN heterojunction (active area is 5 ×5 mm2) for the first time, and Fowler-Nordheim tunneling mechanism has been used to improve device performance. Benefiting from the FNT, under a weak light power of 0.06 mW/cm2, the PSD is able to determine the position of the UV light spot through the output photocurrent difference, displays high precision (0.16 μA/mm), excellent weak light detection capability，and good linearity without power supply. Besides, the Gr/GaN show an ultralow threshold voltage (0.132 V) of FNT. When the bias is higher than 0.132 V, photogenerated carriers will tunneling the thin insulation layer by the FNT, resulting in a multiplication of the photocurrent. Therefore, under the same power densities light irradiation (0.06 mW/cm2), the device exhibits an ultrahigh responsivity of 1.88 A/W, a remarkable detectivity of 2.71 × 1013 Jones, and a high LDR of over 99.58 at 0 V bias. More importantly, as an optoelectronic demodulator the device realizes the decoding of optical signals into electrical signals, showing great potential for application in non-contact measurement systems.

Burnout of emergency nurses in a South African context: the role of job demands and resources, and capabilities.

Emergency nurses are prone to burnout due to the nature of their profession and working environment, potentially putting their sustainable employability at risk and so too the care provided by and success of emergency departments. Psychological research has predominantly focused on samples drawn from western, educated, industrialized, rich, and democratic (WEIRD) societies, concerning a small part of the world population. Consequently, this study investigated emergency nurses' burnout in a non-WEIRD society and assessed the role of job demands-resources and work capabilities on their burnout levels. A total of 204 emergency nurses in a South African context participated in a cross-sectional survey. The Job Demands-Resources Scale, the Capability Set for Work Questionnaire, and the Burnout Assessment Tool-Short Form were administered. Using and developing knowledge and skills and building and maintaining meaningful relationships were the strongest work capabilities of emergency nurses. In contrast, earning a good income, involvement in important decisions, and contributing to something valuable were the weakest capabilities. Latent class analysis resulted in three capability sets: a robust capability set, an inadequate capability set, and a weak capability set. Regarding job resources, emergency nurses with a robust capability set reported better relationships with their supervisors and higher job autonomy than the inadequate and weak capability sets. In addition, emergency nurses with a robust capability set reported better co-worker relationships and better access to good equipment than those with a weak capability set. Nurses with an inadequate capability set experienced significantly more challenging job demands than the other two sets. Finally, nurses with a weak capability set (compared to the robust capability set) experienced significantly higher levels of exhaustion and mental distance. Improving emergency nurses' job resources (especially relationships with co-workers and supervisors, job autonomy, and equipment sufficiency) would increase their capabilities, decreasing their burnout levels, especially exhaustion and mental distance.

The UNEP governance and its challenge towards mechanism of NGO engagement in Indonesia

Since the globalization era and the end of the Cold War, the environment is the third agenda after international security and the global economy (Porter and Brown, 1996). In 1972, the Stockholm Conference, the first global environmental meeting, led to the establishment of the United Nations of Environment Programme (UNEP) in 1974. Its aim was for managing global environmental issues under the mandate of the United Nations. Since 1992, there has been a framework to engage civil societies in the UN system and environmental governance, which is called Major Groups. They are children and youth, women, trade unions, farmers, indigenous communities, scientists, business sectors, and NGOs. This Major Groups regularly hold an annual meeting along with UNEP Governing Council Meeting. However, their representatives have not fully participated in the decision-making process. The main reasons were complicated accreditation for Major Groups, lack of access, lack of financial support, and lack of coordination in terms of doing public consultation with the UNEP Governing Council. In the case of Indonesia, no NGO has been included in UNEP-accredited NGOs (UNEP Document, 2013). The research question is why UNEP governance does not fully influence the NGOs in Indonesia. This paper aims to analyze the factors of the weak UNEP governance using a theoretical framework for civic engagement. In its theory, there are 3 key indicators: information, participation, and consultation. This paper used a qualitative method by collecting data and conducting in-depth interviews with WWF Indonesia, WALHI (Indonesian Environmental Forum), and Indonesia Berkebun (Gardening Indonesia). The key finding of the research is that UNEP has weak capability in doing public consultation and national outreach. Hence, UNEP should create National Committee, which strengthens the link between Indonesian NGOs and ASEAN.