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1. chinaXiv:202011.00140 [pdf]

抑郁症患者的语言使用模式.pdf

黄观澜; 周晓璐
Subjects: Psychology >> Clinical and Counseling Psychology

语言使用模式能反映心理状态和精神病理学特征。抑郁症患者与健康人群的语言使用模式存在差异,识别抑郁症患者的语言使用模式有助于抑郁症的预测和诊断。传统的心理学研究和基于社交媒体的研究均表明,抑郁症患者更多地使用第一人称单数代词和消极情绪词,更少地使用第一人称复数代词和积极情绪词。基于社交媒体的研究进一步发现了一些抑郁个体日常生活中的其他语言标志。建议未来的研究进一步确认更具抑郁特异性的语言标志,并进一步探索语言标志与抑郁症状间的理论联系。

submitted time 2020-11-28 Hits30Downloads11 Comment 0

2. chinaXiv:202011.00141 [pdf]

东西方文化下的真实自我研究:一种关系的视角.pdf

梁燕芳; 谢天
Subjects: Psychology >> Social Psychology

真实自我反映了个体行为与其价值观、信仰、需求等内在状态的一致性程度,分为特质真实与状态真实。在辨析了真实自我与自我认知、自我概念清晰性、自我一致性、正直、真诚等相关概念的异同,并梳理该领域已有理论后,提出真实自我表现或实现的文化差异,即西方文化中的真实自我是自主动机驱动的,而东方文化中的真实自我是关系要求驱动的。未来可以将“关系化”作为现象场,以儒家传统思想为理智资源,从理论建构、社会现象(新兴网络社交平台、社会变迁),以及结合具体的研究方法(如跨文化比较、突显情境变化的方法)等方面开展研究。

submitted time 2020-11-27 Hits22Downloads13 Comment 0

3. chinaXiv:202005.00034 [pdf]

化危为机:青少年学校转折期的过渡

柴晓运; 林丹华
Subjects: Psychology >> Developmental Psychology

从生命历程的角度看,学校过渡是青少年成长过程中的重要发展转折点,对个体的发展轨迹具有重要影响。先前研究多基于缺陷的视角,将学校过渡视为充满挑战和风险的时期,并发现青少年在这一时期伴随着各种消极的发展结果。但从青少年积极发展的视角来看,学校过渡可能是青少年获得适应性的、健康发展的重要机遇,也是发展可塑性表现最为充分的时期。如果青少年的内部和外部资源能够很好的融合,他们就有可能获得积极的学校过渡。

submitted time 2020-11-26 Hits3229Downloads1234 Comment 0

4. chinaXiv:202011.00139 [pdf]

工作场所不文明行为与职场排斥间的螺旋效应

詹思群; 严瑜
Subjects: Psychology >> Management Psychology

工作场所不文明行为与职场排斥间的螺旋效应模型可用道德排除理论和情感事件理论解释。根据道德排除理论遭受工作场所不文明行为会导致受害者与实施者心理距离增加,进而对实施者实施职场排斥;从旁观者视角来看,目睹工作场所不文明行为会影响旁观者的道义公正感和互动公平感进而表现出对实施者的职场排斥,且该中介过程受到利他性的调节。同样,基于情感事件理论,遭受职场排斥会导致职场排斥受害者的消极情绪水平增加促使其成为工作场所不文明行为的实施者。

submitted time 2020-11-26 Hits142Downloads73 Comment 0

5. chinaXiv:202011.00126 [pdf]

Morphological characteristics and dynamic changes of seif dunes in the eastern margin of the Kumtagh Desert, China

PANG,Yingjun; WU,Bo; LI,Yonghua; XIE,Shengbo
Subjects: Physics >> General Physics: Statistical and Quantum Mechanics, Quantum Information, etc.

The seif dune field over the gravel desert surface in the eastern margin of the Kumtagh Desert is a valuable experimental site for the observation of dune formation and dynamics. We used high-resolution remote sensing and station observation approaches, combined with wind and grain size data, to study the characteristics of the aeolian environment and the morphologies of and dynamic changes in seif dunes. We observed the ratio of the resultant drift potential (RDP) to the drift potential (DP), which was 0.37, associated with an obtuse bimodal wind regime. The drift potentials in the west-northwest (WNW) and east-northeast (ENE) directions were dominant, and the angle between the two primary DP directions was 135.00°. The dune orientations ranged from 168.75°–213.75°, which were parallel to the resultant drift direction (186.15°). The dune lengths ranged from 51.68 to 1932.11 m with a mean value of 344.91 m. The spacings of the dunes ranged from 32.34 to 319.77 m with a mean value of 93.39 m. The mean grain size of the sediments became finer, and the sorting became better from upwind tail to downwind tip, which indicated that the sediment of the seif dunes in the study region may be transported from northward to southward. The rate of increase in the length, the mean longitudinal migration rate of the dune tail, and the mean longitudinal extension rate of the dune tip (also called elongation rate) were 4.93, 4.63, and 9.55 m/a, respectively. The mean lateral migration vector of the seif dunes was approximately 0.11 m/a towards the west (–0.11 m/a), while the mean amplitude of lateral migration was 0.53 m/a, ignoring the direction of lateral migration. We found that the seif dune field formed first beside seasonal rivers, which can provide sediment, and then expanded downwind.

submitted time 2020-11-25 From cooperative journals:《Journal of Arid Land》 Hits104Downloads59 Comment 0

6. chinaXiv:202011.00127 [pdf]

Assessing the effects of vegetation and precipitation on soil erosion in the Three-River Headwaters Region of the Qinghai-Tibet Plateau, China

HE,Qian; DAI,Xiao'ai; CHEN,Shiqi
Subjects: Physics >> General Physics: Statistical and Quantum Mechanics, Quantum Information, etc.

Soil erosion in the Three-River Headwaters Region (TRHR) of the Qinghai-Tibet Plateau in China has a significant impact on local economic development and ecological environment. Vegetation and precipitation are considered to be the main factors for the variation in soil erosion. However, it is a big challenge to analyze the impacts of precipitation and vegetation respectively as well as their combined effects on soil erosion from the pixel scale. To assess the influences of vegetation and precipitation on the variation of soil erosion from 2005 to 2015, we employed the Revised Universal Soil Loss Equation (RUSLE) model to evaluate soil erosion in the TRHR, and then developed a method using the Logarithmic Mean Divisia Index model (LMDI) which can exponentially decompose the influencing factors, to calculate the contribution values of the vegetation cover factor (C factor) and the rainfall erosivity factor (R factor) to the variation of soil erosion from the pixel scale. In general, soil erosion in the TRHR was alleviated from 2005 to 2015, of which about 54.95% of the area where soil erosion decreased was caused by the combined effects of the C factor and the R factor, and 41.31% was caused by the change in the R factor. There were relatively few areas with increased soil erosion modulus, of which 64.10% of the area where soil erosion increased was caused by the change in the C factor, and 23.88% was caused by the combined effects of the C factor and the R factor. Therefore, the combined effects of the C factor and the R factor were regarded as the main driving force for the decrease of soil erosion, while the C factor was the dominant factor for the increase of soil erosion. The area with decreased soil erosion caused by the C factor (12.10×103 km2) was larger than the area with increased soil erosion caused by the C factor (8.30×103 km2), which indicated that vegetation had a positive effect on soil erosion. This study generally put forward a new method for quantitative assessment of the impacts of the influencing factors on soil erosion, and also provided a scientific basis for the regional control of soil erosion.

submitted time 2020-11-25 From cooperative journals:《Journal of Arid Land》 Hits99Downloads55 Comment 0

7. chinaXiv:202011.00129 [pdf]

Precipitation forecasting by large-scale climate indices and machine learning techniques

GHOLAMI ROSTAM,Mehdi ; SADATINEJAD,Seyyed Javad ; MALEKIAN,Arash
Subjects: Physics >> General Physics: Statistical and Quantum Mechanics, Quantum Information, etc.

Global warming is one of the most complicated challenges of our time causing considerable tension on our societies and on the environment. The impacts of global warming are felt unprecedentedly in a wide variety of ways from shifting weather patterns that threatens food production, to rising sea levels that deteriorates the risk of catastrophic flooding. Among all aspects related to global warming, there is a growing concern on water resource management. This field is targeted at preventing future water crisis threatening human beings. The very first stage in such management is to recognize the prospective climate parameters influencing the future water resource conditions. Numerous prediction models, methods and tools, in this case, have been developed and applied so far. In line with trend, the current study intends to compare three optimization algorithms on the platform of a multilayer perceptron (MLP) network to explore any meaningful connection between large-scale climate indices (LSCIs) and precipitation in the capital of Iran, a country which is located in an arid and semi-arid region and suffers from severe water scarcity caused by mismanagement over years and intensified by global warming. This situation has propelled a great deal of population to immigrate towards more developed cities within the country especially towards Tehran. Therefore, the current and future environmental conditions of this city especially its water supply conditions are of great importance. To tackle this complication an outlook for the future precipitation should be provided and appropriate forecasting trajectories compatible with this region's characteristics should be developed. To this end, the present study investigates three training methods namely backpropagation (BP), genetic algorithms (GAs), and particle swarm optimization (PSO) algorithms on a MLP platform. Two frameworks distinguished by their input compositions are denoted in this study: Concurrent Model Framework (CMF) and Integrated Model Framework (IMF). Through these two frameworks, 13 cases are generated: 12 cases within CMF, each of which contains all selected LSCIs in the same lead-times, and one case within IMF that is constituted from the combination of the most correlated LSCIs with Tehran precipitation in each lead-time. Following the evaluation of all model performances through related statistical tests, Taylor diagram is implemented to make comparison among the final selected models in all three optimization algorithms, the best of which is found to be MLP-PSO in IMF.

submitted time 2020-11-25 From cooperative journals:《Journal of Arid Land》 Hits114Downloads59 Comment 0

8. chinaXiv:202011.00131 [pdf]

Can climate change influence agricultural GTFP in arid and semi-arid regions of Northwest China?

FENG,Jian; ZHAO,Lingdi; ZHANG,Yibo; SUN,Lingxiao; YU,Xiang; YU,Yang
Subjects: Physics >> General Physics: Statistical and Quantum Mechanics, Quantum Information, etc.

There are eight provinces and autonomous regions (Gansu Province, Ningxia Hui Autonomous Region, Xinjiang Uygur Autonomous Region, Inner Mongolia Autonomous Region, Tibet Autonomous Region, Qinghai Province, Shanxi Province, and Shaanxi Province) in Northwest China, most areas of which are located in arid and semi-arid regions (northwest of the 400 mm precipitation line), accounting for 58.74% of the country's land area and sustaining approximately 7.84×106 people. Because of drought conditions and fragile ecology, these regions cannot develop agriculture at the expense of the environment. Given the challenges of global warming, the green total factor productivity (GTFP), taking CO2 emissions as an undesirable output, is an effective index for measuring the sustainability of agricultural development. Agricultural GTFP can be influenced by both internal production factors (labor force, machinery, land, agricultural plastic film, diesel, pesticide, and fertilizer) and external climate factors (temperature, precipitation, and sunshine duration). In this study, we used the Super-slacks-based measure (Super-SBM) model to measure agricultural GTFP during the period 2000–2016 at the regional level. Our results show that the average agricultural GTFP of most provinces and autonomous regions in arid and semi-arid regions underwent a fluctuating increase during the study period (2000–2016), and the fluctuation was caused by the production factors (input and output factors). To improve agricultural GTFP, Shaanxi, Shanxi, and Gansu should reduce agricultural labor force input; Shaanxi, Inner Mongolia, Gansu, and Shanxi should decrease machinery input; Shaanxi, Inner Mongolia, Xinjiang, and Shanxi should reduce fertilizer input; Shaanxi, Xinjiang, Gansu, and Ningxia should reduce diesel input; Xinjiang and Gansu should decrease plastic film input; and Gansu, Shanxi, and Inner Mongolia should cut pesticide input. Desirable output agricultural earnings should be increased in Qinghai and Tibet, and undesirable output (CO2 emissions) should be reduced in Inner Mongolia, Xinjiang, Gansu, and Shaanxi. Agricultural GTFP is influenced not only by internal production factors but also by external climate factors. To determine the influence of climate factors on GTFP in these provinces and autonomous regions, we used a Geographical Detector (Geodetector) model to analyze the influence of climate factors (temperature, precipitation, and sunshine duration) and identify the relationships between different climate factors and GTFP. We found that temperature played a significant role in the spatial heterogeneity of GTFP among provinces and autonomous regions in arid and semi-arid regions. For Xinjiang, Inner Mongolia, and Tibet, a suitable average annual temperature would be in the range of 7°C–9°C; for Gansu, Shanxi, and Ningxia, it would be 11°C–13°C; and for Shaanxi, it would be 15°C–17°C. Stable climatic conditions and more efficient production are prerequisites for the development of sustainable agriculture. Hence, in the agricultural production process, reducing the redundancy of input factors is the best way to reduce CO2 emissions and to maintain temperatures, thereby improving the agricultural GTFP. The significance of this study is that it explores the impact of both internal production factors and external climatic factors on the development of sustainable agriculture in arid and semi-arid regions, identifying an effective way forward for the arid and semi-arid regions of Northwest China.

submitted time 2020-11-25 From cooperative journals:《Journal of Arid Land》 Hits121Downloads67 Comment 0

9. chinaXiv:202011.00130 [pdf]

Effects of biodegradable mulch on soil water and heat conditions, yield and quality of processing tomatoes by drip irrigation

JIA,Hao; WANG,Zhenhua; ZHANG,Jinzhu; LI,Wenhao; REN,Zuoli; JIA,Zhecheng; WANG,Qin
Subjects: Physics >> General Physics: Statistical and Quantum Mechanics, Quantum Information, etc.

To combat the problem of residual film pollution and ensure the sustainable development of agriculture in oasis areas, a field experiment was carried out in 2019 at the Wuyi Farm Corps Irrigation Center Test Station in Urumqi, Northwest China. Four types of biodegradable mulches, traditional plastic mulchs and a control group (bare land; referred to as CK) were compared, including a total of six different treatments. Effects of mulching on soil water and heat conditions as well as the yield and quality of processing tomatoes under drip irrigation were examined. In addition, a comparative analysis of economic benefits of biodegradable mulches was performed. Principal component analysis and gray correlation analysis were used to evaluate suitable mulching varieties for planting processing tomatoes under drip irrigation. Our results show that, compared with CK, biodegradable mulches and traditional plastic mulch have a similar effect on retaining soil moisture at the seedling stage but significantly increase soil moisture by 0.5%–1.5% and 1.5%–3.0% in the middle and late growth periods (P<0.050), respectively. The difference in the thermal insulation effect between biodegradable mulch and plastic mulch gradually reduces as the crop grows. Compared with plastic mulch, the average soil temperature at 5–20 cm depth under biodegradable mulches is significantly lowered by 2.04°C–3.52°C and 0.52°C–0.88°C (P<0.050) at the seedling stage and the full growth period, respectively, and the water use efficiency, average fruit yield, and production-investment ratio under biodegradable mulches were reduced by 0.89%–6.63%, 3.39%–8.69%, and 0.51%–6.33% (P<0.050), respectively. The comprehensive evaluation analysis suggests that the black oxidized biological double-degradation ecological mulch made from eco-benign plastic is the optimal film type under the study condition. Therefore, from the perspective of sustainable development, biodegradable mulch is a competitive alternative to plastic mulch for large-scale tomato production under drip irrigation in the oasis.

submitted time 2020-11-25 From cooperative journals:《Journal of Arid Land》 Hits127Downloads65 Comment 0

10. chinaXiv:202011.00128 [pdf]

Degradation leads to dramatic decrease in topsoil but not subsoil root biomass in an alpine meadow on the Tibetan Plateau, China

ZHANG,Zhenchao; LIU,Miao; SUN,Jian; WEI,Tianxing
Subjects: Physics >> General Physics: Statistical and Quantum Mechanics, Quantum Information, etc.

Understanding the effects of degradation on belowground biomass (BGB) is essential for assessment of carbon budget of the alpine meadow ecosystem on the Tibetan Plateau, China. This ecosystem has been undergoing serious degradation owing to climate change and anthropogenic activities. This study examined the response of the vertical distribution of plant BGB to degradation and explored the underlying mechanisms in an alpine meadow on the Tibetan Plateau. A field survey was conducted in an alpine meadow with seven sequential degrees of degradation in the Zoige Plateau on the Tibetan Plateau during the peak growing season of 2018. We measured aboveground biomass (AGB), BGB, soil water content (SWC), soil bulk density (SBD), soil compaction (SCOM), soil organic carbon (SOC), soil total nitrogen (STN), soil total phosphorus (STP), soil available nitrogen (SAN), and soil available phosphorus (STP) in the 0–30 cm soil layers. Our results show that degradation dramatically decreased the BGB in the 0–10 cm soil layer (BGB0–10) but slightly increased the subsoil BGB. The main reason may be that the physical-chemical properties of surface soil were more sensitive to degradation than those of subsoil, as indicated by the remarked positive associations of the trade-off value of BGB0–10 with SWC, SCOM, SOC, STN, SAN, and STP, as well as the negative correlation between the trade-off value of BGB0–10 and SBD in the soil layer of 0–10 cm. In addition, an increase in the proportion of forbs with increasing degradation degree directly affected the BGB vertical distribution. The findings suggest that the decrease in the trade-off value of BGB0–10 in response to degradation might be an adaptive strategy for the degradation-induced drought and infertile soil conditions. This study can provide theoretical support for assessing the effects of degradation on the carbon budget and sustainable development in the alpine meadow ecosystem on the Tibetan Plateau as well as other similar ecosystems in the world.

submitted time 2020-11-25 From cooperative journals:《Journal of Arid Land》 Hits136Downloads74 Comment 0

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