An Ultra-Flexible Sodium-Ion Full Cell with High Energy/Power Density and Unprecedented Structural Stability.

Futuristic wearable electronics desperately need power sources with similar flexibility and durability. In this regard, the authors, therefore, propose a scalable PAN-PMMA blend-derived electrospinning protocol to fabricate free-standing electrodes comprised of cobalt hexacyanoferrate nanocube cathode and tin metal organic framework-derived nanosphere anode, respectively, for flexible sodium-ion batteries. The resulting unique inter-networked nanofiber mesh offers several advantages such as robust structural stability towards repeated bending and twisting stresses along with appreciable electronic/ionic conductivity retention without any additional post-synthesis processing. The fabricated flexible sodium ion full cells deliver a high working voltage of 3.0 V, an energy density of 273 Wh·kg-1 , and a power density of 2.36 kW·kg-1 . The full cells retain up to 86.73% of the initial capacity after 1000 cycles at a 1.0 C rate. After intensive flexibility tests, the full cells also retain 78.26% and 90.78% of the initial capacity after 1000 bending and twisting cycles (5 mm radius bending and 40o axial twisting), respectively. This work proves that the proposed approach can also be employed to construct similar robust, free-standing nanofiber mesh-based electrodes for mass-producible, ultra-flexible, and durable sodium ion full cells with commercial viability.

Mapping out the vulnerabilities of migrant women in the informal sector: A qualitative investigation in Dhaka city.

The current study seeks to explore the vulnerabilities typically encountered by female migrants in the informal sector in Dhaka city. It used a qualitative research approach, purposively selecting four areas from Dhaka city. Twenty-five semi-structured in-depth interviews during eight months of participant observation were conducted to accomplish the study objective. The authors used the capability approach theory to elucidate the phenomenon of vulnerability experienced by female migrants in the informal sector. The thematic data analyses were performed using the Granheim approach and NVivo 12 software. The findings of this study suggest that migrant women who work on the street face a number of significant challenges. These challenges include sexual assault and harassment, social stigma and cultural barriers, financial obstacles, and extortion and bribery. The authors recommend that governments provide access to state credits, social security, health insurance, and other forms of social protection for informal sector workers. The finding revealed that informal workers are often excluded from these essential benefits, making it difficult for such workers to expand their businesses or have a safety net in case of illness, unemployment, or other shocks.

Social support: mediating the emotional intelligence-academic stress link.

Introduction: This study examines the relationship between emotional intelligence (EI) and academic stress among tertiary-level students who continued academic activities remotely during the pandemic and the mediating role of social support (SS) in the relationship. Methods: Using a cross-sectional survey design, 429 students studying business, engineering, social science, and science in Bangladesh provided data via Qualtrics. Using the Structural Equation Modeling in SmartPLS 4 (4.0.8.9), we modeled emotional intelligence as the reflective-formative and social support (support from family, friends, and significant other) and perceived academic stress as the reflective-reflective, second-order constructs. We also conducted a one-way between-groups analysis of variance (ANOVA) to investigate the impact of gender (male and female) and current stage of academic study (Undergraduate year one to four and post-graduation) on emotional intelligence and academic stress, respectively. Results and discussion: Results show that all the hypothesized relationships are statistically significant: EI is negatively related to perceived academic stress, and SS significantly mediates the relationship between EI and academic stress. Hence, essential strategies are suggested to help students for managing academic stress.

WheatSpikeNet: an improved wheat spike segmentation model for accurate estimation from field imaging.

Phenotyping is used in plant breeding to identify genotypes with desirable characteristics, such as drought tolerance, disease resistance, and high-yield potentials. It may also be used to evaluate the effect of environmental circumstances, such as drought, heat, and salt, on plant growth and development. Wheat spike density measure is one of the most important agronomic factors relating to wheat phenotyping. Nonetheless, due to the diversity of wheat field environments, fast and accurate identification for counting wheat spikes remains one of the challenges. This study proposes a meticulously curated and annotated dataset, named as SPIKE-segm, taken from the publicly accessible SPIKE dataset, and an optimal instance segmentation approach named as WheatSpikeNet for segmenting and counting wheat spikes from field imagery. The proposed method is based on the well-known Cascade Mask RCNN architecture with model enhancements and hyperparameter tuning to provide state-of-the-art detection and segmentation performance. A comprehensive ablation analysis incorporating many architectural components of the model was performed to determine the most efficient version. In addition, the model's hyperparameters were fine-tuned by conducting several empirical tests. ResNet50 with Deformable Convolution Network (DCN) as the backbone architecture for feature extraction, Generic RoI Extractor (GRoIE) for RoI pooling, and Side Aware Boundary Localization (SABL) for wheat spike localization comprises the final instance segmentation model. With bbox and mask mean average precision (mAP) scores of 0.9303 and 0.9416, respectively, on the test set, the proposed model achieved superior performance on the challenging SPIKE datasets. Furthermore, in comparison with other existing state-of-the-art methods, the proposed model achieved up to a 0.41% improvement of mAP in spike detection and a significant improvement of 3.46% of mAP in the segmentation tasks that will lead us to an appropriate yield estimation from wheat plants.

An application of the participatory approach to develop an integrated water resources management (IWRM) system for the drought-affected region of Bangladesh.

In many cases, poor management of water supplies is to blame for a crisis. Scholars and practitioners have proposed developing enhanced modalities of water governance that promote the implementation of Integrated Water Resources Management (IWRM) to meet the interconnected problems of assuring access to sustainable water supplies for the world's populations. Therefore, this research aims to do two things: 1) evaluate the current status of water and related resources, and 2) create an operational decision-support system for the sustainable use of water resources based on integrated water resources management (IWRM). Beneficiaries are involved in all stages of the planning process, from the first brainstorming to the final evaluation. There hasn't been anything quite like these kinds of efforts before because they do not actively include community groups and government agencies in project design and money distribution. Matching water resources with various users (farmers, fisherman, women, and others) and their agriculture and fisheries development requirements was the focus of this study, which took an integrated participatory approach. Therefore, water management agencies are established through participatory water management. Beneficiaries realized that collective action results in the empowerment of all community members through capacity building and participatory water management. Because of this plan, agricultural progress in the area under consideration will proceed smoothly.

Efficient synergism of NiO-NiSe2 nanosheet-based heterostructures shelled titanium nitride array for robust overall water splitting.

Water splitting via the use of an efficient catalyst is a clean and cost-effective approach to produce green hydrogen. In this study, we successfully developed a novel hybrid coming from thin NiO-NiSe2 nanosheet-based heterostructure shelled high-conductive titanium nitride nanoarrays (TiN@NiO-NiSe2) supported on carbon cloth (CC) via an optimized in-situ synthesis strategy. The hybrid possesses unique physicochemical properties due to the combination of merits from individual components and their synergistic effects, thereby boosting number and type of electroactive sites, reasonably adjusting Gibbs free adsorption energy, and promoting charge/mass transfers. As a potential bifunctional electrocatalyst, the hybrid requires low overpotentials of 115 and 240 mV to reach a current response of 10 mA cm-2 towards hydrogen evolution reaction and oxygen evolution reaction in 1.0 M KOH, respectively. Therefore, an electrolyzer of the TiN@NiO-NiSe2 on CC exhibits a low operation voltage of 1.57 V at 10 mA cm-2 together with a prospective durability, which exceed behaviors of Pt/C//RuO2 as well as recently reported bifunctional electrocatalysts. The results suggest a promising approach for developing cost-effective catalyst towards green hydrogen production via water splitting.