Influence of Climate Change and Anthropogenic Activities on Groundwater Level in the Northern Huangqihai Basin, China

Abstract The variation in the groundwater level, which is an indicative factor that can reflect changes in both groundwater level and groundwater quantity, was selected as the factor to be analyzed. Rainfall and groundwater exploitation were chosen as the representative factors of climate change and anthropogenic activities, respectively. By applying the elastic coefficient method and other mathematical statistical methods, the influence of climate change and anthropogenic activities on groundwater was analyzed qualitatively and quantitatively. The northern Huangqihai basin was chosen as the study area. The rainfall in the study area showed an increasing trend from 1996–2020, while most variations in groundwater level were negative. This result indicated that the positive influence of rainfall on the variation in the groundwater level in the study area was not enough to offset the negative influence of groundwater exploitation. The correlation between anthropogenic activities and variations in the groundwater level was lower in wet years than in normal years but the highest in dry years. Based on the comparative method of the slope changing ratio of cumulative quantity and the elastic coefficient method, it was determined that the contribution rate of climate change to the variation in groundwater level was 22.08% and that of human activities was 77.92%. Thus, the sustainable development of the groundwater environment can be realized by positively guiding anthropogenic activities and minimizing negative influences.

Download Full-text

PENGARUH BENCANA ALAM, PERUBAHAN IKLIM, DAN KUALITAS LINGKUNGAN TERHADAP JUMLAH KUNJUNGAN WISATAWAN MANCANEGARA KE INDONESIA

Jurnal Kajian Ekonomi dan Pembangunan ◽

10.24036/jkep.v1i4.8949 ◽

2019 ◽

Vol 1 (4) ◽

pp. 13

Author(s):

Safitri Safitri ◽

Alpon Satrianto

Keyword(s):

Climate Change ◽

Regression Analysis ◽

Panel Data ◽

Natural Disaster ◽

Significant Influence ◽

Research Result ◽

Negative Influence ◽

Positive Influence ◽

Environment Quality ◽

Research Goal

This research goal is looking for the effect of natural disaster, climate change, and environment quality to the amount of tourist visit to Indonesia. This research uses panel data from 2014 untill 2017, the data get from the related institutions, and uses multiple regression analysis. This research result: 1) Natural disaster has negative influence and it is not significant to tourist visit to Indonesia, 2) Climate change has positive and significant influence to tourist visit to Indonesia, and 3) Environment quality has positive influence and is not significant to the amount of torist visit to Indonesia.

Download Full-text

Stochastic and Artificial Intelligence Models for Climate Change Investigation and Groundwater Level Assessment of Gaza Coastal Aquifer (Palestine)

10.22541/au.161252402.20503328/v1 ◽

2021 ◽

Author(s):

Hassan Al-Najjar ◽

Gokmen Ceribasi ◽

Emrah Dogan ◽

Khalid Qahman ◽

Mazen Abualtayef ◽

...

Keyword(s):

Climate Change ◽

Time Series ◽

Stochastic Models ◽

Groundwater Level ◽

Coastal Aquifer ◽

Anthropogenic Activities ◽

Gaza Strip ◽

Groundwater Abstraction ◽

The Gaza Strip ◽

The Impact

The Gaza coastal aquifer is a critical resource for the supply of water to the Gaza Strip and continues to be depleted as a result of the effects of climate change and the anthropogenic activities. Therefore, this study tends to investigate the impact of climate change and groundwater withdrawal practices on the oscillation of the Gaza Coastal Aquifer water table level by recruiting the power of the stochastic time-series models in exemplifying the autoregression of data and by leveraging the efficiency of the artificial neural networks (ANNs) in expressing the nonlinear regression between the different meteorological and hydrological factors. The climate stochastic models reveal that the Gaza Strip region will face a decline in the precipitation by -5.2% and an increase in the temperature by +1˚C in the timeframe of 2020-2040. The potential evaporation and the sunshine period will increase by about 111 mm and 5 hours, respectively during the next 20 years. However, the atmosphere is predicted to be drier where the relative humidity will fall by a trend of -8% in 20 years. The stochastic models developed for the groundwater abstraction time series show that the groundwater pumping processes would increase by about 55 % by 2040, compared to the 124 million cubic meters of groundwater that was withdrawn in 2020. The stochastic model of structure (2,1,5) (4,1,2)12 was defined to extend the time series of the groundwater level up to 2040. In order to form an integrated stochastic-ANN model, the combination of the time series of climate factors, groundwater abstraction and groundwater level were emerged into a one hidden layer ANN of 20-neurons. The performance of the model was high in term of training and in forecasting the future where the correlation coefficient (r) = 0.95-0.99 and the root mean square error (RMSE) = 0.09-0.21.

Download Full-text

Does Diversity in The Boardroom Add Value to a Firm?

American Journal of Management ◽

10.33423/ajm.v18i5.255 ◽

2018 ◽

Vol 18 (5) ◽

Keyword(s):

Firm Performance ◽

Panel Data ◽

Firm Size ◽

Significant Influence ◽

Negative Influence ◽

Positive Influence ◽

Future Research ◽

Board Composition ◽

Board Diversity

This study examines whether board diversity affects firm performance. We investigate this study using panel data of a sample of S&P 500 firms during a 12 year period. After controlling for industry, firm size, and other board composition variables, we find that all three board diversity variables of interest – gender, ethnicity, and age have a significant influence on firm performance. While ethnicity and age have a positive influence on firm performance, it was found that gender has a negative influence. Implications for future research are discussed.

Download Full-text

Emergence of New Potential Insect Pests of Date Palm: Could Climate Change Be the Reason?

Outlooks on Pest Management ◽

10.1564/v30_dec_02 ◽

2019 ◽

Vol 30 (6) ◽

pp. 242-245

Author(s):

Hamadttu A. F. El-Shafie

Keyword(s):

Climate Change ◽

Date Palm ◽

Insect Pests ◽

Anthropogenic Activities ◽

Economic Damage ◽

South American ◽

Palm Fruit ◽

The Family ◽

American Palm ◽

Sorghum Chafer

Four insect species were reported as new potential pests of date palm in recent years. They are sorghum chafer (Pachnoda interrupta), the rose chafer (Potosia opaca), the sericine chafer beetle (Maladera insanablis), and the South American palm borer (Pysandisia archon). The first three species belong to the order Coleoptera and the family Scarabaeidae, while the fourth species is a lepidopteran of the family Castniidae. The injury as well as the economic damage caused by the four species on date palm need to be quantified. Due to climate change and anthropogenic activities, the date palm pest complex is expected to change in the future. To the author's knowledge, this article provides the first report of sorghum chafer as a pest damaging date palm fruit.

Download Full-text

Concerns or Desires Post-Pandemic: An Extended MGB Model for Understanding South Korean Residents’ Perceptions and Intentions to Travel to China

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph18052542 ◽

2021 ◽

Vol 18 (5) ◽

pp. 2542

Author(s):

Guanghui Qiao ◽

Xiao-li Zhao ◽

Luqi Xin ◽

Seokchool Kim

Keyword(s):

Mass Media ◽

Latent Variables ◽

Structural Equation ◽

Mainland China ◽

Negative Influence ◽

Positive Influence ◽

Extended Model ◽

South Korean ◽

Structural Relationships ◽

China Post

In this study, we examined South Korean residents’ travel-related behavioural intention for mainland China post-COVID-19 using an extended model of goal-directed behaviour. To do so, we integrated South Korean residents’ perceptions of country image (PCI), mass media, and concerns about travel into the framework of the original model of goal-directed behaviour (MGB). Structural equation modelling was used to identify the structural relationships among the latent variables. The results show that mass media had a positive influence on South Korean residents’ perception of China’s image, a negative influence on residents’ concerns, and a positive influence on residents’ behavioural intentions for travel overseas. Meanwhile, PCI had a positive influence on residents’ attitude towards travel overseas. The theoretical and practical implications of the study are discussed.

Download Full-text

Enhancement of the Thermal Performance of the Paraffin-Based Microcapsules Intended for Textile Applications

Polymers ◽

10.3390/polym13071120 ◽

2021 ◽

Vol 13 (7) ◽

pp. 1120

Author(s):

Virginija Skurkyte-Papieviene ◽

Ausra Abraitiene ◽

Audrone Sankauskaite ◽

Vitalija Rubeziene ◽

Julija Baltusnikaite-Guzaitiene

Keyword(s):

Thermal Conductivity ◽

Thermal Performance ◽

Comparative Method ◽

Multiwall Carbon Nanotubes ◽

Acrylic Resin ◽

Positive Influence ◽

Outer Shell ◽

Ir Camera ◽

Spacer Fabric ◽

Thermally Conductive

Phase changing materials (PCMs) microcapsules MPCM32D, consisting of a polymeric melamine-formaldehyde (MF) resin shell surrounding a paraffin core (melting point: 30–32 °C), have been modified by introducing thermally conductive additives on their outer shell surface. As additives, multiwall carbon nanotubes (MWCNTs) and poly (3,4-ethylenedioxyoxythiophene) poly (styrene sulphonate) (PEDOT: PSS) were used in different parts by weight (1 wt.%, 5 wt.%, and 10 wt.%). The main aim of this modification—to enhance the thermal performance of the microencapsulated PCMs intended for textile applications. The morphologic analysis of the newly formed coating of MWCNTs or PEDOT: PSS microcapsules shell was observed by SEM. The heat storage and release capacity were evaluated by changing microcapsules MPCM32D shell modification. In order to evaluate the influence of the modified MF outer shell on the thermal properties of paraffin PCM, a thermal conductivity coefficient (λ) of these unmodified and shell-modified microcapsules was also measured by the comparative method. Based on the identified optimal parameters of the thermal performance of the tested PCM microcapsules, a 3D warp-knitted spacer fabric from PET was treated with a composition containing 5 wt.% MWCNTs or 5 wt.% PEDOT: PSS shell-modified microcapsules MPCM32D and acrylic resin binder. To assess the dynamic thermal behaviour of the treated fabric samples, an IR heating source and IR camera were used. The fabric with 5 wt.% MWCNTs or 5 wt.% PEDOT: PSS in shell-modified paraffin microcapsules MPCM32D revealed much faster heating and significantly slower cooling compared to the fabric treated with the unmodified ones. The thermal conductivity of the investigated fabric samples with modified microcapsules MPCM32D has been improved in comparison to the fabric samples with unmodified ones. That confirms the positive influence of using thermally conductive enhancing additives for the heat transfer rate within the textile sample containing these modified paraffin PCM microcapsules.

Download Full-text

Analysis and Prediction of “AI + Education” Attention Based on Baidu Index—Taking Guizhou Province as an Example

Future Internet ◽

10.3390/fi13050120 ◽

2021 ◽

Vol 13 (5) ◽

pp. 120

Author(s):

Yulin Zhao ◽

Junke Li ◽

Jiang-E Wang

Keyword(s):

Artificial Intelligence ◽

Southwest China ◽

Arima Model ◽

Modern Technology ◽

Guizhou Province ◽

Western Region ◽

Elastic Coefficient ◽

The Sustainable Development ◽

Intelligence Education ◽

Coefficient Method

Studying the attention of “artificial intelligence + education” in ethnic areas is of great significance for China for promoting the integrated development of new educational modes and modern technology in the western region. Guizhou province is an area inhabited by ethnic minorities, located in the heart of Southwest China. The development of its intelligent education has strong enlightenment for the whole country and the region. Therefore, this paper selects the Baidu Index of “artificial intelligence (AI) + education” in Guizhou province from 2013 to 2020, analyzes the spatial–temporal characteristics of its network attention by using the elastic coefficient method, and builds the ARIMA model on this basis to predict future development. The results show that the public’s attention to “AI + education” differs significantly in time and space. Then, according to the prediction results, this paper puts forward relevant suggestions for the country to promote the sustainable development of education in western ethnic areas.

Download Full-text

Filling the void of family leadership: institutional support to business model changes in the Italian Industry 4.0 experience

The Journal of Technology Transfer ◽

10.1007/s10961-021-09847-4 ◽

2021 ◽

Author(s):

Marco Cucculelli ◽

Ivano Dileo ◽

Marco Pini

Keyword(s):

Business Model ◽

Industry 4.0 ◽

Manufacturing Industry ◽

Business Models ◽

Institutional Support ◽

Negative Influence ◽

Positive Influence ◽

External Support ◽

Family Management ◽

Family Leadership

AbstractWe examine whether the probability of innovating a company’s business model towards the Industry 4.0 paradigm is affected by external institutional support and family leadership. Industry 4.0 is the information-intensive transformation of global manufacturing enabled by Internet technologies aimed at reinventing products and services from design and engineering to manufacturing. Using a sample of 3000 firms from a corporate survey on the manufacturing industry in Italy, our results showed that family leadership has a significant positive influence on the adoption of Industry 4.0 business models, but only in terms of family ownership. By contrast, family management has a negative influence on the probability of adopting a new business model. However, this negative influence is almost totally offset by the presence of the Triple Helix, i.e. the external support by public institutions and universities, which counterbalances the lower propensity of family managers to adopt Industry 4.0 business models. This supporting role only occurs when institutions and universities act together.

Download Full-text

An experimental study of the influence of riblets on transition

Journal of Fluid Mechanics ◽

10.1017/s0022112096002315 ◽

1996 ◽

Vol 315 ◽

pp. 31-49 ◽

Cited By ~ 31

Author(s):

G. R. Grek ◽

V. V. Kozlov ◽

S. V. Titarenko

Keyword(s):

Experimental Study ◽

Three Dimensional ◽

Negative Influence ◽

Positive Influence ◽

Linear Stage ◽

Turbulent Transition ◽

Transition Structures ◽

Stage Transition ◽

Tollmien Schlichting ◽

Laminar Turbulent Transition

An experimental study of the effect of riblets on three-dimensional nonlinear structures, the so-called Λ-vortices on laminar-turbulent transition showed that riblets delay the transformation of the Λ-vortices into turbulent spots and shift the point of transition downstream. This result is opposite to the negative influence of such ribbed surfaces on two-dimensional linear Tollmien-Schlichting waves (the linear stage of transition). Thus, the ribbed surface influences laminar-turbulent transition structures differently: a negative influence on the linear-stage transition structures and a positive influence on the nonlinear-stage transition structures. It is demonstrated that transition control by means of riblets requires special attention to be paid to the choice of their location, taking into account the stage of transition.

Download Full-text

Lagged Ensembles, Forecast Configuration, and Seasonal Predictions

Monthly Weather Review ◽

10.1175/mwr-d-12-00184.1 ◽

2013 ◽

Vol 141 (10) ◽

pp. 3477-3497 ◽

Cited By ~ 19

Author(s):

Mingyue Chen ◽

Wanqiu Wang ◽

Arun Kumar

Keyword(s):

Lead Time ◽

Geographical Location ◽

Seasonal Prediction ◽

Skill Score ◽

Negative Influence ◽

Positive Influence ◽

Prediction Skill ◽

Ensemble Size ◽

Seasonal Forecasts ◽

Ensemble Forecasts

Abstract An analysis of lagged ensemble seasonal forecasts from the National Centers for Environmental Prediction (NCEP) Climate Forecast System, version 2 (CFSv2), is presented. The focus of the analysis is on the construction of lagged ensemble forecasts with increasing lead time (thus allowing use of larger ensemble sizes) and its influence on seasonal prediction skill. Predictions of seasonal means of sea surface temperature (SST), 200-hPa height (z200), precipitation, and 2-m air temperature (T2m) over land are analyzed. Measures of prediction skill include deterministic (anomaly correlation and mean square error) and probabilistic [rank probability skill score (RPSS)]. The results show that for a fixed lead time, and as one would expect, the skill of seasonal forecast improves as the ensemble size increases, while for a fixed ensemble size the forecast skill decreases as the lead time becomes longer. However, when a forecast is based on a lagged ensemble, there exists an optimal lagged ensemble time (OLET) when positive influence of increasing ensemble size and negative influence due to an increasing lead time result in a maximum in seasonal prediction skill. The OLET is shown to depend on the geographical location and variable. For precipitation and T2m, OLET is relatively longer and skill gain is larger than that for SST and tropical z200. OLET is also dependent on the skill measure with RPSS having the longest OLET. Results of this analysis will be useful in providing guidelines on the design and understanding relative merits for different configuration of seasonal prediction systems.

Download Full-text