Promoting Sense of Belonging and Interest in Geosciences among Undergraduate Women through Mentoring

The purpose of this study is to investigate whether students’ university sense of belonging mediates the relationship between mentor network diversity and students’ interest development among undergraduate women in STEM majors. The sample for this study was consisted of 277 undergraduate women majoring in a STEM discipline with initial interests in geosciences across nine universities within the United States. A regression-based mediation analysis was performed using the Hayes’ (2013) macro to test the indirect effect of mentor support on interest through university sense of belonging. Consistent with our hypothesis, the analysis revealed a statistically significant and positive indirect effect of the mentor network diversity on interest in geoscience through university sense of belonging, a×b = .04, 95% CI = [.01,.08]. More specifically, the mentor network diversity positively predicts university sense of belonging (B = 0.19,

Uncertain Dynamic Characteristic Analysis for Structures with Spatially Dependent Random System Parameters

This work presents a robust non-deterministic free vibration analysis for engineering structures with random field parameters in the frame of stochastic finite element method. For this, considering the randomness and spatial correlation of structural physical parameters, a parameter setting model based on random field theory is proposed to represent the random uncertainty of parameters, and the stochastic dynamic characteristics of different structural systems are then analyzed by incorporating the presented parameter setting model with finite element method. First, Gauss random field theory is used to describe the uncertainty of structural material parameters, the random parameters are then characterized as the standard deviation and correlation length of the random field, and the random field parameters are then discretized with the Karhunen–Loeve expansion method. Moreover, based on the discretized random parameters and finite element method, structural dynamic characteristics analysis is addressed, and the probability distribution density function of the random natural frequency is estimated based on multi-dimensional kernel density estimation method. Finally, the random field parameters of the structures are quantified by using the maximum likelihood estimation method to verify the effectiveness of the proposed method and the applicability of the constructed model. The results indicate that (1) for the perspective of maximum likelihood estimation, the parameter setting at the maximum value point is highly similar to the input parameters; (2) the random field considering more parameters reflects a more realistic structure

Unimodal Training-Multimodal Prediction: Cross-modal Federated Learning with Hierarchical Aggregation

Multimodal learning has seen great success mining data features from multiple modalities with remarkable model performance improvement. Meanwhile, federated learning (FL) addresses the data sharing problem, enabling privacy-preserved collaborative training to provide sufficient precious data. Great potential, therefore, arises with the confluence of them, known as multimodal federated learning. However, limitation lies in the predominant approaches as they often assume that each local dataset records samples from all modalities. In this paper, we aim to bridge this gap by proposing an Unimodal Training - Multimodal Prediction (UTMP) framework under the context of multimodal federated learning. We design HA-Fedformer, a novel transformer-based model that empowers unimodal training with only a unimodal dataset at the client and multimodal testing by aggregating multiple clients' knowledge for better accuracy. The key advantages are twofold. Firstly, to alleviate the impact of data non-IID, we develop an uncertainty-aware aggregation method for the local encoders with layer-wise Markov Chain Monte Carlo sampling. Secondly, to overcome the challenge of unaligned language sequence, we implement a cross-modal decoder aggregation to capture the hidden signal correlation between decoders trained by data from different modalities. Our experiments on popular sentiment analysis benchmarks, CMU-MOSI and CMU-MOSEI, demonstrate that HA-Fedformer significantly outperforms state-of-the-art multimodal models under the UTMP federated learning frameworks, with 15%-20% improvement on most attributes.Comment: 10 pages,5 figure

Global-regional nested simulation of particle number concentration by combing microphysical processes with an evolving organic aerosol module

Aerosol microphysical processes are essential for the next generation of global and regional climate and air quality models to determine particle size distribution. The contribution of organic aerosols (OAs) to particle formation, mass, and number concentration is one of the major uncertainties in current models. A new global–regional nested aerosol model was developed to simulate detailed microphysical processes. The model combines an advanced particle microphysics (APM) module and a volatility basis set (VBS) OA module to calculate the kinetic condensation of low-volatility organic compounds and equilibrium partitioning of semi-volatile organic compounds in a 3-D framework using global–regional nested domain. In addition to the condensation of sulfuric acid, the equilibrium partitioning of nitrate and ammonium, and the coagulation process of particles, the microphysical processes of the OAs are realistically represented in our new model. The model uses high-resolution size bins to calculate the size distribution of new particles formed through nucleation and subsequent growth. The multi-scale nesting enables the model to perform high-resolution simulations of the particle formation processes in the urban atmosphere in the background of regional and global environments. By using the nested domains, the model reasonably reproduced the OA components obtained from the analysis of aerosol mass spectrometry measurements through positive matrix factorization and the particle number size distribution in the megacity of Beijing during a period of approximately a month. Anthropogenic organic species accounted for 67 % of the OAs of secondary particles formed by nucleation and subsequent growth, which is considerably larger than that of biogenic OAs. On the global scale, the model well predicted the particle number concentration in various environments. The microphysical module combined with the VBS simulated the universal distribution of organic components among the different aerosol populations. The model results strongly suggest the importance of anthropogenic organic species in aerosol particle formation and growth at polluted urban sites and over the whole globe.Aerosol microphysical processes are essential for the next generation of global and regional climate and air quality models to determine particle size distribution. The contribution of organic aerosols (OAs) to particle formation, mass, and number concentration is one of the major uncertainties in current models. A new global-regional nested aerosol model was developed to simulate detailed microphysical processes. The model combines an advanced particle microphysics (APM) module and a volatility basis set (VBS) OA module to calculate the kinetic condensation of low-volatility organic compounds and equilibrium partitioning of semi-volatile organic compounds in a 3-D framework using global-regional nested domain In addition to the condensation of sulfuric acid, the equilibrium partitioning of nitrate and ammonium, and the coagulation process of particles, the microphysical processes of the OAs are realistically represented in our new model. The model uses high-resolution size bins to calculate the size distribution of new particles formed through nucleation and subsequent growth. The multi-scale nesting enables the model to perform high-resolution simulations of the particle formation processes in the urban atmosphere in the background of regional and global environments. By using the nested domains, the model reasonably reproduced the OA components obtained from the analysis of aerosol mass spectrometry measurements through positive matrix factorization and the particle number size distribution in the megacity of Beijing during a period of approximately a month. Anthropogenic organic species accounted for 67 % of the OAs of secondary particles formed by nucleation and subsequent growth, which is considerably larger than that of biogenic OAs. On the global scale, the model well predicted the particle number concentration in various environments. The microphysical module combined with the VBS simulated the universal distribution of organic components among the different aerosol populations. The model results strongly suggest the importance of anthropogenic organic species in aerosol particle formation and growth at polluted urban sites and over the whole globe.Peer reviewe

Role modeling is a viable retention strategy for undergraduate women in the geosciences

Gender diversity leads to better science; however, a number of science, technology, engineering, and mathematics (STEM) disciplines, including many geoscience subdisciplines, show a persistent gender gap. PROmoting Geo- science Research, Education, and SuccesS (PROGRESS) is a theory-driven role modeling and mentoring program aimed at supporting undergraduate women interested in geoscience-related degree and career pathways. This study is unique because it is being conducted in a long-term applied setting, rather than as a laboratory exercise. We compare female STEM majors in PROGRESS to a matched control group (N = 380) using a longitudinal prospec- tive multisite quasi-experimental design. College women in PROGRESS par- ticipated in a mentoring and role-modeling weekend workshop with follow- up support, while women in the control group participated in neither the workshop nor the follow-up support. PROGRESS members identified more female STEM career role models than controls (60% versus 42%, respectively), suggesting that deliberate interventions can develop the networks of under- graduate women. Undergraduate women that participate in PROGRESS have higher rates of persistence in geoscience-related majors (95% versus 73%), although the rates of switching into a geoscience-related major did not differ across groups. More strikingly, we also find that the persistence of undergrad- uate women in geoscience-related majors is related to the number of female STEM career role models they identify, as their odds of persisting approxi- mately doubles for each role model they identify. We conclude that our ability to retain undergraduate women in the geosciences will depend, in part, on helping them to identify same-gender career role models. Further, the suc- cess of PROGRESS points to steps universities and departments can take to sustain their students’ interest and persistence, such as hosting interactive panels with diverse female scientists to promote the attainability and social relevance of geoscience careers

Research on the sustainable development of tourism coupled with economic and environment data——a case study of Hangzhou

The scale of tourism has continued to expand in recent years, and many associated activities cause damage to the natural environment. The tourism, economy and natural environment constitute a system: destruction of the natural environment reduces the value of tourism and a lack of tourism affects the development of the economy. To explore the relationship between the tourism, economy and natural environment, and to explore possibilities for sustainable development, this paper takes Hangzhou, a tourist city in China, as a research object. An analysis of time series data is carried out. First, the tourism, economy and natural environment subsystems are constructed by extracting time series data acquired between 2010 and 2020. Second, a tourism evaluation model with coupled economic and natural environment data is constructed and the coupling degree and coupling coordination level in Hangzhou are evaluated. Third, the time series of each subsystem and the coupling coordination level of the whole system are analyzed. Finally, an optimization strategy is proposed for the coupled coordinated development of the tourism, economy and natural environment in Hangzhou. A key result is that the tertiary industry represented by tourism has become the main source of local income. Hangzhou's tourism coupling coordination level has changed from slight disorder in 2010 to good in 2020. It is also found that the COVID-19 pandemic has become a major factor restricting the development of tourism. Before the outbreak of COVID-19, Hangzhou's tourism industry and economy were synchronized. After the outbreak of COVID-19, both the number of tourists and tourism revenue in Hangzhou fell by nearly 15%

Effects of natural covers on soil evaporation of the shelterbelt along the Tarim Desert Highway

The control of soil evaporation is one of important approaches to save water. The artificially simulated evaporation experiments have been conducted in the hinterland of the Taklimakan Desert to reveal the effects of the natural covers on the soil evaporation of the Tarim Desert Highway shelterbelt as well as provide some insights in the efficient utilization of water resources and optimization of irrigation systems. The results showed that (1) All the covers, including the sand deposit, the salt crust, the litter, the sand-litter mixed layer and so on, can significantly inhibit the soil water evaporation. Specifically, the daily evaporation, the total evaporation, and the evaporation rate in covered sands were much smaller than that of sands without cover. The cover inhibition effects increased with the cover thickness. Particularly, the soil evaporation of the covered sands was less affected by external and internal factors than that of the bare sands. Moreover, the variation of daily evaporation of covered sands was smaller than that of bare sands. The cumulative evaporation varied linearly with time in the covered sands whereas it varied logarithmically in the bare sands. In addition, the soil evaporation in the bare sands showed significantly different characteristics in the early and late stages of the evaporation. (2) All the covers exhibited the significant inhibiting effect on the soil evaporation, and the inhibition efficiency increased logarithmically with the cover thickness. However, as the cover thickness was above a certain value, the increase in the inhibition efficiency was slow. Particularly, at a cover thickness of 2 cm, there was no obvious difference in the inhibition efficiency among all kinds of covers. The maximum inhibition efficiency as calculated from the daily evaporation on the first day of irrigation was: sand-litter mixed layer (79.92%) > litter layer (78.96%) > salt crust (75.58%) > sand bed (74.11%), whereas the average inhibiting efficiency as calculated from the cumulative soil evaporation at the end of an irrigation cycle (the fourth day) was: salt crust (67.78%) > sand-litter mixed layer (66.72%) > sand deposit (63.28%) > litter layer (61.74%)

Classification and regionalization of the forming environment of windblown sand disasters along the Tarim Desert Highway

Through the systematic field survey and observations, the factor quantification as well as setting the criteria, the sand disaster-forming environment along the Tarim Desert Highway can be divided into four grades by the classification and regionalization based on fuzzy mathematics. The length of the regions with significant sand disaster accounted for 37.1% of the total highway length. Particularly, the area along the Tarim Desert Highway, based on the sand disaster-forming environment classification as well as the difference in the five basic landform units along the highway, combined with the difference of wind regime, can be divided into five regions, in which the length of the regions suffering severe sand damage occupied 64.3% of the total highway length. In addition, the index of disaster formation grade along the highway decreased from north to south, showing a repeated spatial pattern in small length scales

Finishing the euchromatic sequence of the human genome

The sequence of the human genome encodes the genetic instructions for human physiology, as well as rich information about human evolution. In 2001, the International Human Genome Sequencing Consortium reported a draft sequence of the euchromatic portion of the human genome. Since then, the international collaboration has worked to convert this draft into a genome sequence with high accuracy and nearly complete coverage. Here, we report the result of this finishing process. The current genome sequence (Build 35) contains 2.85 billion nucleotides interrupted by only 341 gaps. It covers ∼99% of the euchromatic genome and is accurate to an error rate of ∼1 event per 100,000 bases. Many of the remaining euchromatic gaps are associated with segmental duplications and will require focused work with new methods. The near-complete sequence, the first for a vertebrate, greatly improves the precision of biological analyses of the human genome including studies of gene number, birth and death. Notably, the human enome seems to encode only 20,000-25,000 protein-coding genes. The genome sequence reported here should serve as a firm foundation for biomedical research in the decades ahead

Ordering Strategy for Fresh Agricultural Products in External Financing Condition

This paper firstly introduced the two stage supply chain consisting of single agricultural product producer and fund restraint retailer. Then, it analyzed the influence of bank interest rate on order quantity, wholesale price and expected profit of retailer and producer on the condition of retailer taking external loan strategy. Studies have shown that when the bank interest rate is in (0, 0.9), the order quantity of agricultural products is a decreasing function of bank interest rate; when the bank interest rate is in (0, 1), wholesale price of agricultural products decreases with increase in the bank interest rate; when the bank interest rate is in (0, 0.6), the expected profit of retailer is a decreasing function of bank interest rate; when the bank interest rate is in (0, 1), the expected profit of producer decreases with increase in the bank interest rate. Finally, through simulation calculation examples, it verified suitability of the conclusion, in the hope of providing reference and application value for management of supply chain