Distinct Phases Research Articles

Actor-agency and institutional complexity: multinational corporations’ strategies to combat the framework convention on tobacco control in Brazil

Purpose This study aims to analyse the strategic moves used by major tobacco corporations to thwart the ratification of the World Health Organization’s Framework Convention on Tobacco Control (FCTC) in Brazil. Design/methodology/approach The authors conducted a detailed historical case study spanning 1988–2005 and encompassing the period leading up to Brazil’s FCTC ratification. The authors collected qualitative data from various sources to triangulate and develop a comprehensive historical account. Findings The historical analysis identified three distinct phases. First, the acquisition of a Brazilian cigarette factory, Souza Cruz, by British American Tobacco dramatically altered power dynamics, strengthening the position of the tobacco industry. The second phase regards the era of dictatorship and the efforts of various actors advocating against smoking and the tobacco industry. The third phase involved Brazil’s re-democratisation and the challenges of securing FCTC ratification, during which fierce industry opposition had to be overcome. Throughout these phases, the authors identified four key strategies used by multinational corporations (MNCs) in Brazil to uphold unsustainable practices and products that contradicted public interests instead of reforming them: shaping collective memory, dissimulation, re-presentation and redirecting attention. Originality/value This study contributes to critical international business research on emerging economies by examining how Brazil’s position in the global capitalist system has influenced its dependency and how MNCs produce and maintain cycles of poverty and unsustainable practices through the exploitation of power dynamics within the country.

Development and validation of a structured questionnaire for assessing risk factors of medication non-adherence among pulmonary tuberculosis patients in Indonesia.

Background: Medication non-adherence is a significant concern in tuberculosis (TB) treatment, requiring a precise understanding of the associated risk factors. However, there is a lack of appropriate means to assess the risk factors among TB patients in Indonesia, leading to the development and validation of a structured questionnaire for this purpose. Method: This study unfolded in two distinct phases, namely, the first included questionnaire construction through framework development, item generation, item screening, and pretesting (in 50 patients). The second comprised questionnaire validation with 346 participants using confirmatory factor analysis (CFA) and structural equation modeling-partial least squares (SEM-PLS). Additionally, reliability testing was conducted using Cronbach's alpha and composite reliability statistical techniques. Results: In the development phase, 168 items were defined, consisting of sociodemographic characteristics (8 items) and risk factors for medication non-adherence (160 items). Expert evaluation reduced the number of items to 60, which decreased to 22 after performing a pilot study. Subsequent SEM-PLS modeling resulted in the identification of 14 valid items, representing five major risk factors, namely, socioeconomics (4 items), healthcare team (4 items), condition (3 items), therapy (2 items), and patient (1 item). Only condition-related factors were found to influence non-adherence, and all constructs showed good reliability based on Cronbach's alpha (>0.6) and composite reliability (0.7) values. Conclusion: The final 22 items that emerged from this rigorous process indicated a valid and robust questionnaire for assessing risk factors of medication non-adherence among pulmonary tuberculosis patients in Indonesia. The developed questionnaire was positioned to be a valuable tool for healthcare professionals, policymakers, and scientists in creating patient-centered strategies and interventions to address non-adherence.

Crystal Structure, Morphology, and Magnetic Properties of Magnetic Nanocomposites with Iron Oxide Core and Zinc Oxide/Titanium Oxide Shell

In this work, we successfully synthesized a magnetic nanocomposite material (Fe3O4@ZnO/TiO2) with an iron oxide core and a zinc oxide/TiO2 shell (Fe3O4@ZnO/TiO2). The purpose of this study was to characterize the Crystal Structure, Morphology, and Magnetic Properties of Magnetic Nanocomposites with Iron Oxide Core and Zinc Oxide/Titanium Oxide Shell. The crystal structure of the sample was analyzed using X-ray diffraction, which identified three distinct phases: Fe3O4, ZnO, and TiO2. These phases respectively exhibited cubic spinel, hexagonal wurtzite, and tetragonal crystal structures. Transmission Electron Microscopy (TEM) characterization confirmed that the sample had a magnetic core–shell structure, with superparamagnetic properties and excellent stability owing to its spinel cubic structure, which is the primary magnetic material structure of the sample. The successful formation of the Fe3O4@ZnO/TiO2 nanocomposite represents a significant advancement in the synthesis of materials. This could serve as a basis for further investigations into magnetic materials, opening up possibilities for their application across diverse fields.

Exploring plasmonic gradient metasurfaces for enhanced optical sensing in the visible spectrum

Abstract While conventional optical sensors hold historical significance, they face inherent limitations in sensitivity, operational intricacies, and bulky size. A breakthrough in this realm comes from the advent of metasurface sensors, which leverage nanoscale optical effects, thereby expanding the horizons of optical sensing applications. However, past methods employed in metasurface sensors predominantly rely on wavelength shifts or intensity changes with high-Q resonances, thereby significantly restricting the detection bandwidth. In response to these challenges, this study introduces a plasmonic gradient metasurface-based sensor (PGMS) designed for refractive index detection across a wide wavelength spectrum. Through the utilization of the Pancharatnam–Berry phase method, the PGMS achieves a distinctive 2π phase shift, facilitating the simultaneous generation of specular and deflected beams. The introduction of a far-field intensity ratio (I* = I +1/I 0) amplifies the change in optical response by maximizing the deflected beam’s intensity while minimizing specular reflection. Experimental validation attests to the PGMS’s consistent performance across diverse media and wavelengths, successfully overcoming challenges associated with oxidation issues. Furthermore, the incorporation of a normalization factor enhances the PGMS’s sensing performance and versatility for broadband optical sensing, accommodating variations in the refractive index. Particularly sensitive in green wavelengths, the PGMS demonstrates its potential in visible spectrum applications, such as biomedical diagnostics and environmental monitoring. This research not only addresses challenges posed by conventional sensors but also propels optical sensing technologies into a realm of heightened sensitivity and adaptability.

Understanding the dynamics of hybrid seed adoption among smallholder chilli farmers in Indonesia

In the realm of agricultural research, considerable attention has been directed toward the adoption of hybrid seeds; however, the evolution of adoption behaviors over time remains an area of limited comprehension. This study contributes to the existing literature by elucidating the determinants that underlies the dynamic of hybrid seed adoption among smallholder chilli farmers in Indonesia. By categorizing adoption into four distinct phases—non-adoption, late-adoption, continual-adoption, and dis-adoption—a nuanced understanding of the phenomenon is sought. Leveraging a two-period panel dataset encompassing chilli farmers, we employ a multinomial logit model to explicate the dynamic adoption behaviors exhibited by these farmers. Our empirical findings bring to light a notable divergence in the variables associated with continual-adoption as opposed to those linked with late-adoption. This distinction underscores the heterogeneous nature of adopters and emphasizes the need for tailored strategies for each category. Specifically, we unearth a positive correlation between membership in a farmer's group and the propensity for continual-adoption, concurrently mitigating the likelihood of non-adoption. The implications drawn from our study underscore the intricate nature of adoption stages, thereby providing valuable insights to inform the design of targeted adoption policies that cater to the distinct strategies required for varying adoption categories.

Analytical modeling of phase change in a composite wall comprising two distinct phase change materials in series

Most of the past literature on solid-liquid phase change heat transfer modeling focuses on a single phase change material (PCM), whereas, a sandwich of two or more PCMs arranged in series may be of interest in several applications. The modeling of heat transfer and phase change in such a system is complicated by the presence of multiple phase change fronts propagating at the same time. This work presents a theoretical analysis of the problem of melting of a two-PCM stack being heated from one end. Depending on whether the lower-melting PCM is located next to or away from the heat source, two distinct cases are considered. The propagation of the phase change fronts in each case is divided into several stages, each of which is characterized by a distinct phase change and/or sensible heating processes. The transient temperature field in each stage is determined in the form of infinite series solutions, and the propagation of phase change front over time is then determined using energy conservation at the phase change interface. In this manner, explicit expressions are derived for the time taken for each layer to completely melt. Results are shown to be in good agreement with finite-element simulations, and with the exact Stefan solution under special conditions. Key non-dimensional parameters that influence the nature of the two-PCM phase change process are identified, and their impact on phase change performance is analyzed. Quantitative predictions are presented for the conditions under which both PCMs finish melting at the same time, which is a favorable outcome for efficient energy storage.

Dual-sided melting of a one-dimensional composite wall comprising two distinct phase change material (PCM) layers

Past literature on theoretical modeling of solid-liquid phase change heat transfer mostly addresses a single phase change material (PCM), whereas, a series combination of two or more PCMs is often used in practical applications. This work presents an approximate analytical model for the melting/freezing of a one-dimensional composite of two PCMs being heated/cooled from both ends. It is shown that up to three phase change fronts may simultaneously exist in this problem. In addition to direct melting/freezing from the respective walls, it is shown that each PCM may also melt/freeze due to heat transfer through the other PCM. Using a quasi-stationary assumption, temperature field during the multi-stage phase change process is approximated by solving a multilayer transient thermal conduction problem using eigenfunction expansion. Good agreement with numerical simulations, and with the Stefan solution for a special case is demonstrated. The impact of key non-dimensional parameters on performance metrics including total time for phase change is determined. A quantitative prediction of conditions leading to the thermodynamically favorable situation of simultaneous completion of phase change of two commonly used PCMs is carried out. This work improves the theoretical understanding of phase change in composite PCMs, leading to optimization of practical thermal systems.

Revisiting the role of HR in the age of AI: bringing humans and machines closer together in the workplace.

The functions of human resource management (HRM) have changed radically in the past 20 years due to market and technological forces, becoming more cross-functional and data-driven. In the age of AI, the role of HRM professionals in organizations continues to evolve. Artificial intelligence (AI) is transforming many HRM functions and practices throughout organizations creating system and process efficiencies, performing advanced data analysis, and contributing to the value creation process of the organization. A growing body of evidence highlights the benefits AI brings to the field of HRM. Despite the increased interest in AI-HRM scholarship, focus on human-AI interaction at work and AI-based technologies for HRM is limited and fragmented. Moreover, the lack of human considerations in HRM tech design and deployment can hamper AI digital transformation efforts. This paper provides a contemporary and forward-looking perspective to the strategic and human-centric role HRM plays within organizations as AI becomes more integrated in the workplace. Spanning three distinct phases of AI-HRM integration (technocratic, integrated, and fully-embedded), it examines the technical, human, and ethical challenges at each phase and provides suggestions on how to overcome them using a human-centric approach. Our paper highlights the importance of the evolving role of HRM in the AI-driven organization and provides a roadmap on how to bring humans and machines closer together in the workplace.

Solute solvent interaction study on 9,9-dihydroxynanoic acid by DFT, IR, Raman, UV, MEP, quantum parameters and docking studies

Density functional quantum mechanical research yield a comprehensive theoretical approach on the selected organic molecule of 9,9-dihydroxynanoic acid. The DFT approach is implemented to optimise the molecular structure. The geometrical parameters of molecule were calculated. The vibrational spectrum studies were done with FT-IR and FT-Raman and their results were investigated. VEDA software is utilised to simulate PED for the basic vibrational frequencies in order to find all the vibration modes. UV–Vis analysis is performed for the gaseous phase and on solvent phases such as water, ethanol, ethyl ethanoate, acetone, and DMSO by TD-DFT-B3LYP with 6-311++G (d,p), and band gap energies are calculated. FMO investigations reported analysing the compound energy gap, softness, hardness, and electrophilicity index in gaseous phase along with a variety solvent phase. To further understand the molecule's reactive areas, Mulliken atomic charge evaluation, Fukui functions, and dual descriptors were conceptually investigated. The electro static MEP map of the compound in distinct solvent phases is provided in order to comprehend the molecular shape, size, and reactive region. The molecule's hyperpolarizability is observed to be 201.8 a.u for gas, 146.6 a.u for acetone, 138.9 a.u for DMSO, 136.3 a.u for water, and 169.8 a.u for ethyl ethanoate, will supports the molecule is good NLO material. The donor acceptor interaction has been explored so as to explain the intramolecular hyper conjugative interaction and stability. To understand the topology Multiwfn analysis like ELF, LOL and ALIE were done. The E.coli proteins are downloaded from the PDB database and fictitiously docked with our selected ligand molecule using Auto Dock software to determine hydrogen bonding and binding energy.

Clinical and molecular profiling of human visceral adipose tissue reveals impairment of vascular architecture and remodeling as an early hallmark of dysfunction

Adipose tissue dysfunction is more related to insulin resistance than body mass index itself and an alteration in adipose tissue function is thought to underlie the shift from metabolically healthy to unhealthy obesity. Herein, we performed a clustering analysis that revealed distinct visceral adipose tissue gene expression patterns in patients with obesity at distinct stages of metabolic dysregulation. We have built a cross-sectional cohort that aims at reflecting the evolution of the metabolic sequelae of obesity with the main objective to map the sequential events that play a role in adipose tissue dysfunction from the metabolically healthy (insulin-sensitive) state to several incremental degrees of metabolic dysregulation, encompassing insulin resistance establishment, pre-diabetes, and type 2 diabetes. We found that insulin resistance is mainly marked by the downregulation of adipose tissue vasculature remodeling-associated gene expression, suggesting that processes like angiogenesis and adaptative expansion/retraction ability suffer early dysregulation. Prediabetes was characterized by compensatory growth factor-dependent signaling and increased response to hypoxia, while type 2 diabetes was associated with loss of cellular response to insulin and hypoxia and concomitant upregulation of inflammatory markers. Our findings suggest a putative sequence of dysregulation of biological processes that is not linear and has multiple distinct phases across the metabolic dysregulation process, ultimately culminating in the climax of adipose tissue dysfunction in type 2 diabetes. Several studies have addressed the transcriptomic changes in adipose tissue of patients with obesity. However, to the best of our knowledge, this is the first study unraveling the potential molecular mechanisms associated with the multi-step evolution of adipose tissue dysfunction along the metabolic sequelae of obesity.

Effect of Mo addition on interfacial microstructure and mechanical property of SiC joint brazed by an Ni–Si filler

AbstractNi‐based alloys provide good brazing filler characteristics for the many applications of SiC ceramics. Nevertheless, the presence of graphite is unavoidable in the reaction between Ni and SiC, leading to a significant degradation of the mechanical properties of the joint. This study investigates the effect of Mo in Ni–30Si alloy on the brazing of SiC at 1300°C, to regulate interfacial reactions and reduce residual stresses by decreasing overall coefficient of thermal expansion (CTE) values throughout the brazing process. The addition of Mo up to 8 at.% efficiently suppresses graphite accumulation by converting it into Mo2C + Ni3Mo3C phases and lowering the CTE to 5.4 × 10−6/°C. When the Mo loading exceeds 12 at.%, the interactions between the filler and SiC are reduced as a result of the non‐homogeneous dispersion of Mo. The experimental findings indicate that the joint without graphite has a lap shear strength of 107 MPa, which is nearly three times greater than the joint with graphite. Thermodynamic analyses are performed to provide a comprehensive understanding of the underlying mechanisms responsible for the formation of distinct phases in brazed joints.

Deep learning-based video-analysis of instrument motion in microvascular anastomosis training.

Attaining sufficient microsurgical skills is paramount for neurosurgical trainees. Kinematic analysis of surgical instruments using video offers the potential for an objective assessment of microsurgical proficiency, thereby enhancing surgical training and patient safety. The purposes of this study were to develop a deep-learning-based automated instrument tip-detection algorithm, and to validate its performance in microvascular anastomosis training. An automated instrument tip-tracking algorithm was developed and trained using YOLOv2, based on clinical microsurgical videos and microvascular anastomosis practice videos. With this model, we measured motion economy (procedural time and path distance) and motion smoothness (normalized jerk index) during the task of suturing artificial blood vessels for end-to-side anastomosis. These parameters were validated using traditional criteria-based rating scales and were compared across surgeons with varying microsurgical experience (novice, intermediate, and expert). The suturing task was deconstructed into four distinct phases, and parameters within each phase were compared between novice and expert surgeons. The high accuracy of the developed model was indicated by a mean Dice similarity coefficient of 0.87. Deep learning-based parameters (procedural time, path distance, and normalized jerk index) exhibited correlations with traditional criteria-based rating scales and surgeons' years of experience. Experts completed the suturing task faster than novices. The total path distance for the right (dominant) side instrument movement was shorter for experts compared to novices. However, for the left (non-dominant) side, differences between the two groups were observed only in specific phases. The normalized jerk index for both the right and left sides was significantly lower in the expert than in the novice groups, and receiver operating characteristic analysis showed strong discriminative ability. The deep learning-based kinematic analytic approach for surgical instruments proves beneficial in assessing performance in microvascular anastomosis. Moreover, this methodology can be adapted for use in clinical settings.

Analyzing the Impact of Simulated Nitrogen Deposition on Stoichiometric Properties and Yield of Ma Bamboo (Dendrocalamus latiflorus Munro) Shoots, Leaves, and Soil Substrate

The growth dynamics of Ma bamboo (Dendrocalamus latiflorus Munro) are intricately linked to nitrogen availability, a pivotal nutrient. Escalating global nitrogen deposition, primarily driven by anthropogenic factors, is reshaping nutrient fluxes and productivity within forest and bamboo ecosystems. Such alterations bear significant implications for the growth equilibrium and yields of rapid-growth species such as Ma bamboo, thereby influencing their sustainable management strategies. This investigation delves into the responses of Ma bamboo under varying nitrogen deposition scenarios (0 g·clump−1, 11.2 g·clump−1, 13.5 g·clump−1, and 22.5 g·clump−1), examining stoichiometric attributes in bamboo shoots, leaves, and soil across distinct growth phases. Our empirical findings reveal that in the early growth stage, nitrogen enrichment markedly augmented N and P concentrations in the foliage and shoots, alongside a corresponding enhancement in soil P content. This was paralleled by a substantial reduction in the C:N ratio in leaves and the C:P ratio in shoots and soil, indicating an amplified uptake of P and N in both plant and soil matrices. During the middle stage, all nitrogen treatments boosted nitrogen levels across various plant tissues, while concurrently, soil C content exhibited a notable decline with increased nitrogen supplementation. In the late stage, leaf and soil N content continued to ascend; however, alterations in C content in both soil and leaves were not pronounced. Contrastingly, N and P levels in shoots showed a gradual decrement. Yield assessments disclosed that during the early stage, the N3 treatment (22.5 g·clump−1) not only delayed shoot emergence by 14 days but also surged the yield by 115.87% in comparison to the control (CK). In the late stage, the N2 treatment (13.5 g·clump−1) extended emergence duration by 10 days, with the yield apex under N3 treatment (22.5 g·clump−1) evidencing a 116.67% yield augmentation over CK. In summation, this study elucidates the stoichiometric balancing and distribution strategies within the plant–soil system of Ma bamboo, investigating its adaptability and responsive feedback to diverse nitrogen deposition gradients. This research contributes to a deeper understanding of plant nutrient adaptation mechanisms in the context of nitrogen deposition, enriches the discourse on plant population stoichiometry, and offers valuable insights and scientific underpinnings for broader-scale community or ecosystem stoichiometry studies.

Analysing the differential impact of the COVID-19 pandemic on the resilience of the tourism economy: A case study of the Chengdu-Chongqing urban agglomeration in China

The outbreak of the COVID-19 pandemic in 2019 had a profound impact on the tourism economy, underscoring the critical importance of assessing and analyzing tourism economic resilience. Traditionally, prior research predominantly focused on constructing evaluation systems based on three dimensions: Risk preparedness capability, Restoration capability, and Reorganization and modernization capacity. In this study, we take an innovative approach by incorporating urban network thinking and establishing a tourism economic network, while introducing the dimension of “The rationality of network structure.” To comprehensively understand the dynamics of tourism economic resilience, we divided the period from 2018 to 2021 into three distinct phases: Stable period, Pre-shock period, and Shock period. This division allowed us to conduct comparative research that highlights the variations in tourism economic resilience across these different time frames. Additionally, we employed advanced methods, such as kernel density estimation and the GTWR model, for empirical analysis of tourism economic resilience within the Chengdu-Chongqing city cluster. The results of our research unveiled that Chengdu and Chongqing both demonstrate a remarkable level of resilience within their tourism economies. However, given their status as the “dual core” of the Chengdu-Chongqing city agglomeration, they are inherently more susceptible to significant fluctuations when confronted with shocks. The spatial pattern of tourism economic resilience is characterized by prominent wings on both sides, a North-South balance, and a central region with vulnerabilities. The predominant evolutionary patterns are marked by multi-level stabilization, moderate growth, and moderate decline. Ziyang is an exceptional region within the broader growth zone, and its reduced risk preparedness capability has led to an overall decline in tourism economic resilience. Furthermore, key influencing factors, including the economy, infrastructure, and ecological environment, exhibit significant spatial heterogeneity. In conclusion, our study offers valuable insights into researching tourism economic resilience under external shocks, such as the COVID-19 pandemic. These findings can be instrumental in guiding policymakers as they develop effective strategies to bolster tourism economic resilience.

Polypyrrole-modified flax fiber sponge impregnated with fatty acids as bio-based form-stable phase change materials for enhanced thermal energy storage and conversion

In this study, we integrated organic phase change materials, decanoic acid (DA) and palmitic acid (PA), into bio-based samples made from sodium alginate (SA) and flax fiber (FF). We also synthesized conductive polypyrrole (PPy) coating through in situ polymerization to create two thermal energy storage and conversion systems with distinct phase change temperatures (32 °C and 63 °C). The PPy coating exhibited uniform polymerization, resulting in electrical conductivity (1.52 ± 0.07 S/m) and thermal conductivity (0.453 ± 0.02 W/mK). The conductive sponge, similar to the plain sponge, had a porous microstructure (85 % porosity) that allowed successful impregnation of 60 % and 74 % of DA and PA, resulting in outstanding energy storage and conversion properties. Specifically, the conductive sponges with DA and PA achieved phase change enthalpies of 100.98 J/g and 154.52 J/g, respectively. DA/PPy@Sponge demonstrated exceptional durability after thermal cycling tests. Furthermore, the conductive sample efficiently converted electrical energy into thermal energy along the conductive path, making it suitable for storing generated heat as both sensible and latent heat, as well as capturing and storing solar energy. Overall, the developed conductive phase change materials offer shape stabilization, high thermal energy storage capacity, and efficient electric/photo-to-thermal conversion properties. These attributes make them promising candidates for diverse applications in energy harvesting, storage, and management in electronics, buildings, transportation, and other relevant fields.

From Granary to Arts Incubator: An Evolutionary Perspective on the Concept of Food for Thought

Does our food for thought come virtually from the internet? When we take a long view, the instant stroke of a keyboard pales in comparison to the centuries-old evolution of real food harvesting and the generation and exchange of ideas, which have resulted in creative capital. The vernacular architecture of the agricultural built environment has almost dematerialized in its transition from the ancient pre-industrial era to the post-truth world, to become almost only an imagined concept. The symbology of the common threshing terrace of a Portuguese remote mountain village can now be found in multiple spaces of the urban realm, including in the metaphor of a community arts incubator’s modus operandi in Albany, New York (USA). How has the concept of food for thought developed and materialized? How has it evolved? And what are some of the expected ways it might be utilized in the future? The purpose of the paper is to trace the evolution of this concept and its elements via the BLC Framework. The methodology employs a time analysis of approximately three centuries to distinguish three distinct evolutionary phases: (i) the pre-industrial era, (ii) the industrial era, and (iii) the information-driven era. The key finding is an up-to-date discussion of the food for thought concept in two distinct geographical worlds and three-time eras, as well as a set of lessons learned according to a protest poem and a rock song. The results are presented in the form of five lessons learned with implications for public policy: the first two lessons pertain to issues of procedural justice as encapsulated in the anonymous ‘The Goose’ poem, while the last three result from a discussion of selected verses in Nick Cave’s ‘Fable of the Brown Ape’ rock song.

Using sprouting behaviour to quantify physiological ageing of seed tubers of potato (Solanum tuberosum L.)

The physiological age of potato seed tubers evolves with chronological age, influenced by growth history and storage conditions. Effective quantification of physiological ageing requires a dynamic and flexible modelling approach. In this study, we conducted three cycles of field production and storage of seed tubers, using contrasting and widely grown cultivars. Different storage temperatures were employed as the sole treatment to introduce variation in the physiological age of the same cultivar. Throughout the storage seasons, periodic assessments of sprouting behaviour were conducted, both at the onset and at the end of a sprouting test. The total sprout dry weight per tuber produced in the sprouting test emerged as the best measure of seed tuber vigour, exhibiting cultivar-specific responses to storage temperatures. To capture these diverse sprouting behaviours, we devised a piecewise sprouting behaviour function. This is the first mathematical model that effectively describes the evolving sprouting patterns and provides biologically relevant parameters for the analysis of cultivar-specific sprouting trends. The temporal parameters of the function displayed sensitivity to storage temperature and year-to-year variation in growth conditions, highlighting distinct physiological phases. Consequently, the function facilitated insightful analysis of these key factors, enabling interpretation of underlying processes involved in the physiological ageing of potato seed tubers.

Electrospun carbon nanofibers embedded with heterostructured NiFe2O4/Fe0.64Ni0.36 nanoparticles as an anode for high-performance lithium-ion battery

Binary transition metal compounds exhibit promising application potential as anode materials in the field of lithium-ion batteries (LIBs) due to their high theoretical specific capacity. However, their poor electrical conductivity and drastic volume expansion during charge and discharge pocesses limit their high-performance applications. Herein, we have synthesized carbon nanofibers (CNFs) loaded with heterostructured NiFe based nanoparticles (NiFe2O4/Fe0.64Ni0.36@CNFs) using electrospinning, and explore their cyclic stability and rate performances. By subjecting the electrospun membranes to thermal treatment at different annealing temperatures, three distinct phases of NiFe compounds embedded in CNFs, i.e., NiFe2O4 (400 °C), NiFe2O4/Fe0.64Ni0.36 (500 °C) and Fe0.64Ni0.36 (800 °C), are obtained. When they are used as anode materials, the electrochemical properties are investigated. The NiFe2O4/Fe0.64Ni0.36@CNFs anode material exhibits the best cycling and rate performances, with a capacity of 431.1 mAh g−1 achieved after 200 cycles at a current density of 0.2 A g−1. Moreover, its specific capacities are 558.9, 400.1, 272.4, 178.1 and 89.5 mAh g−1 at current densities of 0.1, 0.2, 0.5, 1.0 and 2.0 A g−1, respectively. As the current density returns to 0.1 A g−1, its specific discharge capacity can reach 527.5 mAh g−1. The excellent cycling and rate performances of NiFe2O4/Fe0.64Ni0.36@CNFs are mainly attributed to the following reasons: i) the carbon fibers can effectively alleviate volume expansion and structural stress during cycling; ii) Fe0.64Ni0.36 alloy can inhibit the formation of lithium dendrites and effectively reduce the nucleation overpotential of metallic lithium, thereby improving the electrochemical stability; iii) the heterostructure can improve electrochemical properties through the synergistic interaction between NiFe2O4 and Fe0.64Ni0.36. The catalytic Fe0.64Ni0.36 not only facilitate the conversion reaction of NiFe2O4, resulting in the high capacity, but also increase the conductivity of the material. This work offers a feasible strategy to significantly improve the electrochemical performance of binary metal compounds, paving the way for their practical applications in the high-performance LIBs.

Three distinct metabolic phases of polychlorinated biphenyls/biphenyl degrader Acidovorax sp. KKS102 in nutrient broth.

Acidovorax sp. KKS102 is a beta-proteobacterium capable of degrading polychlorinated biphenyls (PCBs). In this study, we examined its growth in liquid nutrient broth supplemented with different carbon sources. KKS102 had at least 3 distinct metabolic phases designated as metabolic phases 1-3, with phase 2 having 2 sub-phases. For example, succinate, fumarate, and glutamate, known to repress the PCB/biphenyl catabolic operon in KKS102, were utilized in phase 1, while acetate, arabinose, and glycerol in phase 2, and glucose and mannose in phase 3. We also showed that the BphQ response regulator mediating catabolite control in KKS102, whose expression level increased moderately through the growth, plays important roles in carbon metabolism in phases 2 and 3. Our study elucidates the hierarchical growth of KKS102 in nutrient-rich media. This insight is crucial for studies exploiting microbial biodegradation capabilities and advancing studies for catabolite regulation mechanisms.

How pre-service teachers change their view of forms of inquiry after participating in an inquiry-based practicum

This study explores how pre-service teachers understand inquiry before and after an inquiry-based practicum and identify which key learning experiences (KLEs) were conducive to inquiry. A survey (n = 57) and a semistructured interview (n = 23) were conducted. Results showed that pre-service teachers' forms of inquiry increased in frequency and complexity after the practicum. The KLE that made their understanding of inquiry more complex was the systematization of the inquiry process into distinct phases. This study reinforces the need to implement an inquiry-based practicum in pre-service teacher training and provides guidance on which learning activities should be prioritized during the practicum.