Aqueous zinc-ion batteries are realistic candidates as stationary storage systems for power-grid applications. However, to accelerate their commercialization, some important challenges must be ...specifically tackled, and appropriate experimental practices need to be embraced to align the academic research efforts with the realistic industrial working conditions for stationary storage. Within this commentary article, both the open challenges and the good experimental practices are discussed in relation to their impact on the future development of the aqueous Zn-ion technology.Aqueous Zn-based batteries represent a viable and cost-effective technology for electricity grid storage. Here, the authors discuss the most challenging aspects to bridge academic and industrial research and accelerate the adoption of this class of devices on a large scale.
•A metric adversarial domain adaptation approach is proposed to successfully achieve cross-domain RUL prediction.•A feature extraction scheme with a dual self-attention module is developed to learn ...features with multi-scale semantics.•A supervised positive contrastive module is designed to maximize the target-specific mutual information.
Many existing domain adaptation-based methods try to derive domain invariant features to address domain shifts and obtain satisfactory remaining useful life (RUL) of bearings under multiple working conditions. However, most methods may not consider local semantics about degradation features and mutual information from target-specific data when aligning distribution discrepancies, thus resulting in limitations. Additionally, the use of contrastive learning to maintain mutual information may introduce unstable negative samples. To overcome these issues, a metric adversarial domain adaptation approach (MADA) is proposed to evaluate the bearing RULs under multiple working conditions. More specifically, an adversarial domain adaptation architecture with a supervised positive contrastive module is developed to consider mutual information without a negative sample, further learning domain invariant features. Also, the dual self-attention module is designed to extract multi-scale contextual semantics between degradation features. Meanwhile, extensive experiments are conducted in twelve cross-domain scenarios for two bearing cases. The experimental results show that the proposed method is more competitive.
The promoted activity and enhanced selectivity of electrocatalysts is commonly ascribed to specific structural features such as surface facets, morphology, and atomic defects. However, unraveling the ...factors that really govern the direct electrochemical reduction of CO2 (CO2RR) is still very challenging since the surface state of electrocatalysts is dynamic and difficult to predict under working conditions. Moreover, theoretical predictions from the viewpoint of thermodynamics alone often fail to specify the actual configuration of a catalyst for the dynamic CO2RR process. Herein, we re‐survey recent studies with the emphasis on revealing the dynamic chemical state of Cu sites under CO2RR conditions extracted by in situ/operando characterizations, and further validate a critical link between the chemical state of Cu and the product profile of CO2RR. This point of view provides a generalizable concept of dynamic chemical‐state‐driven CO2RR selectivity that offers an inspiration in both fundamental understanding and efficient electrocatalysts design.
A critical link between the dynamic chemical state of Cu sites (mixed Cu+‐ and Cu0‐, Cu+‐, and Cu0‐dominated) and their unique selectivity toward the direct electrochemical reduction of CO2 (yielding C2H4/C2H5OH, CO/HCOO−, and CH4, respectively) is put forward. This may be a valuable tool for fine‐tuning the Cu surface state toward distinct CO2RR pathways.
...conditions such as free accommodation, free meals, and maid service, which suggest valued and respected employees, are replaced with the grudging provision of limited mileage allowance for on-call ...shifts, which suggests that employees are viewed as commodities whose long term loyalty and morale are of no consequence.
The deregulation policies implemented in the United States and the European Union in the early 1980s brought forth a significant rise in employment in the field of logistics but at the same ...contributed to a deterioration of work conditions in the industry – a paradoxical situation largely invisible to many in the age of online shopping. In recent years, a number of cinematographers showed interest in this type of work, depicting it in documentaries. Referring to one of these films, The Weight of Dreams (Francesco Mattuzzi, 2015), this review analyses the implications of the deregulation policies over work conditions, focusing on the relation between workers and space. As seen in the film, work in the field of logistics is a struggle between the desire for an efficient movement of goods and the desires of the humans who move the goods. This translates into an ambivalence of the space they use, which on the one hand, is planned for movement, but on the other, is appropriated by users with the illusion of a sedentary life.
Commuting can be tiring and stressful. An unavoidable part of life for many people, it is almost always associated with negative outcomes. This study examined the implications of commuting time for ...the commitment and well-being of employees. This paper uses 'conservation of resources' theory and job demands-resources approaches to argue that employees with long commutes will be less committed and experience lower well-being. These effects are also expected to be mediated by the work-life balance of the employees and interact with the level of autonomy they perceive themselves to have. Data from the fifth European Working Conditions Survey indicate that there is a negative relationship between commuting time, commitment and well-being. Results also suggest that work-life balance mediates part of these relationships and, finally, that autonomy can act as a buffer against the effects of commuting time on both commitment and well-being.
The culture of academic medicine may foster mistreatment that disproportionately affects individuals who have been marginalized within a given society (minoritized groups) and compromises workforce ...vitality. Existing research has been limited by a lack of comprehensive, validated measures, low response rates, and narrow samples as well as comparisons limited to the binary gender categories of male or female assigned at birth (cisgender).
To evaluate academic medical culture, faculty mental health, and their relationship.
A total of 830 faculty members in the US received National Institutes of Health career development awards from 2006-2009, remained in academia, and responded to a 2021 survey that had a response rate of 64%. Experiences were compared by gender, race and ethnicity (using the categories of Asian, underrepresented in medicine defined as race and ethnicity other than Asian or non-Hispanic White, and White), and lesbian, gay, bisexual, transgender, queer (LGBTQ+) status. Multivariable models were used to explore associations between experiences of culture (climate, sexual harassment, and cyber incivility) with mental health.
Minoritized identity based on gender, race and ethnicity, and LGBTQ+ status.
Three aspects of culture were measured as the primary outcomes: organizational climate, sexual harassment, and cyber incivility using previously developed instruments. The 5-item Mental Health Inventory (scored from 0 to 100 points with higher values indicating better mental health) was used to evaluate the secondary outcome of mental health.
Of the 830 faculty members, there were 422 men, 385 women, 2 in nonbinary gender category, and 21 who did not identify gender; there were 169 Asian respondents, 66 respondents underrepresented in medicine, 572 White respondents, and 23 respondents who did not report their race and ethnicity; and there were 774 respondents who identified as cisgender and heterosexual, 31 as having LGBTQ+ status, and 25 who did not identify status. Women rated general climate (5-point scale) more negatively than men (mean, 3.68 95% CI, 3.59-3.77 vs 3.96 95% CI, 3.88-4.04, respectively, P < .001). Diversity climate ratings differed significantly by gender (mean, 3.72 95% CI, 3.64-3.80 for women vs 4.16 95% CI, 4.09-4.23 for men, P < .001) and by race and ethnicity (mean, 4.0 95% CI, 3.88-4.12 for Asian respondents, 3.71 95% CI, 3.50-3.92 for respondents underrepresented in medicine, and 3.96 95% CI, 3.90-4.02 for White respondents, P = .04). Women were more likely than men to report experiencing gender harassment (sexist remarks and crude behaviors) (71.9% 95% CI, 67.1%-76.4% vs 44.9% 95% CI, 40.1%-49.8%, respectively, P < .001). Respondents with LGBTQ+ status were more likely to report experiencing sexual harassment than cisgender and heterosexual respondents when using social media professionally (13.3% 95% CI, 1.7%-40.5% vs 2.5% 95% CI, 1.2%-4.6%, respectively, P = .01). Each of the 3 aspects of culture and gender were significantly associated with the secondary outcome of mental health in the multivariable analysis.
High rates of sexual harassment, cyber incivility, and negative organizational climate exist in academic medicine, disproportionately affecting minoritized groups and affecting mental health. Ongoing efforts to transform culture are necessary.
Automatic and reliable fault diagnosis of rotating machinery cross working conditions is of practical importance. For this purpose, ensemble transfer convolutional neural networks (CNNs) driven by ...multi-channel signals are proposed in this paper. Firstly, a series of source CNNs modified with stochastic pooling and Leaky rectified linear unit (LReLU) are pre-trained using multi-channel signals. Secondly, the learned parameter knowledge of each individual source CNN is transferred to initialize the corresponding target CNN which is then fine-tuned by a few target training samples. Finally, a new decision fusion strategy is designed to flexibly fuse each individual target CNN to obtain the comprehensive result. The proposed method is used to analyze multi-channel signals measured from rotating machinery. The comparison result shows the superiorities of the proposed method over the existing deep transfer learning methods.
•CNN is modified with stochastic pooling and Leaky rectified linear unit.•Multi-channel signals are used to pre-train a series of CNNs.•Transfer CNN is constructed with parameter transfer strategy.•A new decision fusion strategy is designed based on flexible weight assignment.
The world of work is changing. Communications technologies and digital platforms have enabled some types of work to be delivered from anywhere in the world by anyone with a computer and an internet ...connection. This digitally-mediated work brings jobs to parts of the world traditionally characterized by low incomes and high unemployment rates. As such, it has been touted by governments, third-sector organizations, and the private sector as a novel strategy of economic development. Drawing on a four-year study with 65 workers in South Africa, Kenya, Nigeria, Ghana and Uganda, we examine the development implications of the gig economy on labour in Africa. We offer four analytical development dimensions through which platform-based remote work impacts the lives and livelihoods of African workers, i.e. freedom, flexibility, precarity and vulnerablity. We argue that these dimensions should be understood in a continuum to better explain the working conditions and lives of workers in the gig economy.
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