Research on the politics and governance of coal phase-out has primarily concentrated on national-level policymaking and the role of coal in electricity generation. This study examines an urban transitions and multilevel policy mix impacting the Finnish energy company Helen’s transition away from coal, leading to a coal phase-out in the City of Helsinki. Heating presents a major challenge in the shift toward renewable energy sources due to long heating seasons and district heating relying on coal. We integrate a co-evolutionary framework of policy subsystems and socio-technical change with a framework of policy mixes. Our empirical investigation focuses on the effects of multi-level policies that accelerated energy transitions from 2016 to 2021. Through semi-structured interviews with municipal decision-makers, company representatives, and stakeholders, as well as document analysis, we examine the policy instrument mix to better understand multi-level policies and the political environment influencing the energy company. Our analysis points toward four key issues that jointly made a coal phase-out achievable despite significant challenges, and can act as lessons of transitions in other contexts. First, a robust mix of strong destructive policies at various levels rendered coal burning economically unfeasible, while innovative measures created a path forward. Second, personnel changes facilitated the transition. Third, viable technological alternatives to coal were emerging. Fourth, public demand for climate action was intensifying. Our findings suggest that the credibility and comprehensiveness of the policy mix are more crucial than coherence or consistency.
Postharvest light treatments can enhance anthocyanin accumulation in berry fruit, but the extent to which these responses depend on developmental stage at harvest remains poorly understood. This study evaluated the effects of blue, red, and wide-spectrum white light applied for 7 or 14 days to cranberry (Vaccinium macrocarpon) fruit harvested at the green, white, and turning stages. Anthocyanin accumulation was strongly influenced by harvest maturity and light spectrum. Blue light induced the greatest anthocyanin accumulation in fruit harvested at the green and white stages and was accompanied by increased expression of the late anthocyanin biosynthetic genes ANS (anthocyanidin synthase) and UFGT (UDP-glucose:flavonoid 3-O-glucosyltransferase). In turning-stage fruit, all light treatments enhanced anthocyanin accumulation relative to darkness. Changes in skin color closely mirrored anthocyanin accumulation across treatments. Metabolite profiling further revealed contrasting responses among phenolic subclasses: anthocyanins responded strongly to postharvest illumination, whereas proanthocyanidins were influenced primarily by harvest maturity and showed limited responsiveness to light treatments. Flavonols exhibited intermediate, compound-specific responses. In contrast, total phenolics, soluble solids, and titratable acidity were only minimally affected by postharvest illumination and largely followed developmental trends. Ethylene evolution was stimulated by all light treatments in green fruit, showed a transient increase under blue light in white fruit, and was unaffected in turning fruit. These findings demonstrate that the effects of postharvest spectral illumination on cranberry fruit are strongly dependent on harvest maturity and differ among flavonoid subclasses.
Background Cortical processing of proprioceptive-dominant afference arising from the knee joint is largely unknown. Magnetoencephalography (MEG) can be used to quantify the cortical processing of the proprioceptive afference, but MEG-compatible and well-controlled stimulation of the knee joint is technically challenging, and thus has received less attention. New method We introduced a novel MEG-compatible stimulator that delivers controlled patellar tendon taps and elicits proprioceptive-dominant afferent input to the cortex in the knee joint. The stimulus intensity is adjustable, allowing graded activation of proprioceptive input and, when required, elicitation of the patellar-tendon reflex. Results The novel stimulator elicited clear muscular and cortical responses in both intensity conditions. Cortical responses demonstrated moderate to excellent intersession reliability for peak evoked field amplitude (ICC: 0.69–0.96), beta suppression (0.89–0.90) and beta rebound (0.96–0.97). Notably, beta suppression peaked more laterally than expected in both hemispheres. Peak EMG amplitudes in VL and VM muscles were reliable for both intensity conditions (ICC: 0.66–0.89), and stimulus kinematics remained consistent throughout measurements. Comparison with existing methods Previous robotic or motor-driven devices have been used to evoke cortical responses to knee-joint proprioceptive stimulation, but mechanical coupling across adjacent joints may limit knee-specific input. The present stimulator provides a mechanically simple and MEG-compatible tool that targets proprioceptive-dominant afferents of the knee joint more directly, reduces distal joint involvement. Conclusion The novel stimulator is a feasible and repeatable tool for studying cortical processing of proprioceptive afference from the knee joint using MEG.
Customer education in sales (CEd) is an emerging research area, yet the literature remains fragmented across multiple fields with inconsistent terminology and conceptualizations. This fragmentation has hindered the development of cumulative knowledge and left fundamental questions about CEd’s effectiveness, mechanisms, and theoretical foundations unanswered. We conduct a systematic literature review of 42 journal articles, examining CEd research across four dimensions: (1) industry contexts and business settings, (2) delivery modes and their outcomes, (3) mechanisms and boundary conditions, and (4) the application of pedagogical theories. Our analysis reveals that across seven distinct delivery modes, CEd generally produces positive, sales-supporting outcomes, such as customer loyalty. Frontline interactions are the most studied mode, while formal programs show the strongest return on investment. However, significant gaps remain: B2C research predominates, direct financial outcomes are understudied, and few studies engage with pedagogical theory. We offer several avenues for future research.
Electronic nose (e-nose) and electronic tongue (e-tongue) are among the most modern olfactory and gustatory bionic systems that have been able to compensate for the limitations of the human olfactory and gustatory system. These bionic systems have been very successful in evaluating and measuring the quality of food. The enose is capable of evaluating the quality of food through the detection of volatile organic compounds (VOCs) and the e-tongue applies electrochemical methods to assess food quality. Unfortunately, nowadays food fraud is frequently practiced especially in spices that are offered in powdered form in the market. The purpose of this piece of research is thus to evaluate e-nose and e-tongue systems and use machine learning techniques to measure the authenticity and quality of ginger powder. In this study, chickpea powder was used as an adulterant to combine with ginger powder. Ginger powder and fraud samples were prepared in 7 classes (pure chickpea powder, pure ginger powder, 10%, 20%, 30%, 40% and 50% fraud in ginger powder using chickpea powder). Finally, the features extracted from the samples were evaluated and classified using basic CNN, improved CNN, PCA, MLP, Fuzzy, SVM, KNN, GBT and EDT algorithms. The results showed that the e-nose and e-tongue systems in combination with the improved CNN were able to classify the ginger powder and the fraud samples with accuracies of 95.24% and 100%, respectively. In the e-nose system, TGS2620, TGS822 and TGS2610 sensors, and in the e-tongue system, gold and platinum sensors had the strongest performance in detecting and distinguishing ginger powder and fraud samples.
