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Savannahs are often branded by livestock grazing with resulting land degradation. Holistic management of livestock was proposed to contribute to biodiversity conservation by simulating native wildlife grazing behaviour. This study attempts the comparison of the impact of a holistic management regime to a wildlife grazing management regime on grass and ground-dwelling beetle species diversity on neighboring farms in Namibian rangeland. Results show that the response of biodiversity in species richness and composition to holistic management of livestock differs substantially from wildlife grazing with a positive impact. From a total of 39 identified species of ground-dwelling beetles (Coleoptera: Tenebrionidae, Carabidae) from 29 genera, eight species were found to be indicators for holistic management of livestock and three were found to be indicators for wildlife grazed rangeland. Observations suggest that holistic management of livestock may contribute to biodiversity conservation, but the differential effect of grazing management on species assemblages suggests that livestock grazing cannot replace native wildlife herbivory. Implications for insect conservation An adaptive management strategy such as holistic management used in this study shows the potential to support high beetle biodiversity. Holistic management of livestock thus aspects in favour for a sustainable form of grazing management for insect conservation even though it does not functionally replace grazing by native wildlife.
Ionic liquids are well known for their high gas absorption capacity. It is shown that this is not a solvent constant, but can be enhanced by another factor of 10 by pore confinement, here of the ionic liquid (IL) 1-ethyl-3-methylimidazolium acetate (EmimOAc) in the pores of carbon materials. A matrix of four different carbon compounds with micro- and mesopores as well as with and without nitrogen doping is utilized to investigate the influence of the carbons structure on the nitrogen uptake in the pore-confined EmimOAc. In general, the absorption is most improved for IL in micropores and in nitrogen-doped carbon. This effect is so large that it is already seen in TGA and DSC experiments. Due to the low vapor pressure of the IL, standard volumetric sorption experiments can be used to quantify details of this effect. It is reasoned that it is the change of the molecular arrangement of the ions in the restricted space of the pores that creates additional free volume to host molecular nitrogen.
Chelating agents are an integral part of transition metal complex chemistry with broad biological and industrial relevance. The hexadentate chelating agent ethylenediaminetetraacetic acid (EDTA) has the capability to bind to metal ions at its two nitrogen and four of its carboxylate oxygen sites. We use resonant inelastic X-ray scattering at the 1s absorption edge of the aforementioned elements in EDTA and the iron(III)-EDTA complex to investigate the impact of the metal-ligand bond formation on the electronic structure of EDTA. Frontier orbital distortions, occupation changes, and energy shifts through metal- ligand bond formation are probed through distinct spectroscopic signatures.
In crystalline and amorphous semiconductors, the temperature-dependent Urbach energy can be determined from the inverse slope of the logarithm of the absorption spectrum and reflects the static and dynamic energetic disorder. Using recent advances in the sensitivity of photocurrent spectroscopy methods, we elucidate the temperature-dependent Urbach energy in lead halide perovskites containing different numbers of cation components. We find Urbach energies at room temperature to be 13.0 +/- 1.0, 13.2 +/- 1.0, and 13.5 +/- 1.0 meV for single, double, and triple cation perovskite. Static, temperature-independent contributions to the Urbach energy are found to be as low as 5.1 ?+/- 0.5, 4.7 +/- 0.3, and 3.3 +/- 0.9 meV for the same systems. Our results suggest that, at a low temperature, the dominant static disorder in perovskites is derived from zero-point phonon energy rather than structural disorder. This is unusual for solution-processed semiconductors but broadens the potential application of perovskites further to quantum electronics and devices.
Pandemic depression
(2022)
We investigate the effect of the COVID-19 pandemic on self-employed people’s mental health. Using representative longitudinal survey data from Germany, we reveal differential effects by gender: whereas self-employed women experienced a substantial deterioration in their mental health, self-employed men displayed no significant changes up to early 2021. Financial losses are important in explaining these differences. In addition, we find larger mental health responses among self-employed women who were directly affected by government-imposed restrictions and bore an increased childcare burden due to school and daycare closures. We also find that self-employed individuals who are more resilient coped better with the crisis.
We propose a global geomagnetic field model for the last 14 thousand years, based on thermoremanent records. We call the model ArchKalmag14k. ArchKalmag14k is constructed by modifying recently proposed algorithms, based on space-time correlations. Due to the amount of data and complexity of the model, the full Bayesian posterior is numerically intractable. To tackle this, we sequentialize the inversion by implementing a Kalman-filter with a fixed time step. Every step consists of a prediction, based on a degree dependent temporal covariance, and a correction via Gaussian process regression. Dating errors are treated via a noisy input formulation. Cross correlations are reintroduced by a smoothing algorithm and model parameters are inferred from the data. Due to the specific statistical nature of the proposed algorithms, the model comes with space and time-dependent uncertainty estimates. The new model ArchKalmag14k shows less variation in the large-scale degrees than comparable models. Local predictions represent the underlying data and agree with comparable models, if the location is sampled well. Uncertainties are bigger for earlier times and in regions of sparse data coverage. We also use ArchKalmag14k to analyze the appearance and evolution of the South Atlantic anomaly together with reverse flux patches at the core-mantle boundary, considering the model uncertainties. While we find good agreement with earlier models for recent times, our model suggests a different evolution of intensity minima prior to 1650 CE. In general, our results suggest that prior to 6000 BCE the data is not sufficient to support global models.
We examine the relationship between different types of power investments and regional economic dynamics. We construct a novel panel dataset combining data on regional GDP and power capacity additions for different technologies between 1960 and 2015, which covers 65% of the global power capacity that has been installed in this period. We use an event study design to identify the effect of power capacity addition on GDP per capita, exploiting the fact that the exact amount of power capacity coming online each year is determined by random construction delays. We find evidence that GDP per capita increases by 0.2% in the 6 years around the coming online of 100 MW coal-fired power capacity. We find similar effects for hydropower capacity, but not for any other type of power capacity. The positive effects are regionally bounded and stronger for projects on new sites (green-field). The magnitude of this effect might not be comparable to the total external costs of building new coal-fired power capacity, yet our results help to explain why policymakers favor coal investments for spurring regional growth.
The use of neural networks is considered as the state of the art in the field of image classification. A large number of different networks are available for this purpose, which, appropriately trained, permit a high level of classification accuracy. Typically, these networks are applied to uncompressed image data, since a corresponding training was also carried out using image data of similar high quality. However, if image data contains image errors, the classification accuracy deteriorates drastically. This applies in particular to coding artifacts which occur due to image and video compression. Typical application scenarios for video compression are narrowband transmission channels for which video coding is required but a subsequent classification is to be carried out on the receiver side. In this paper we present a special H.264/Advanced Video Codec (AVC) based video codec that allows certain regions of a picture to be coded with near constant picture quality in order to allow a reliable classification using neural networks, whereas the remaining image will be coded using constant bit rate. We have combined this feature with the ability to run with lowest latency properties, which is usually also required in remote control applications scenarios. The codec has been implemented as a fully hardwired High Definition video capable hardware architecture which is suitable for Field Programmable Gate Arrays.
Forced to stay at home
(2022)
The effects of COVID-19-related lockdowns on deterioration of mental health and use of exercise to remediate such effects has been well documented in numerous populations. However, it remains unknown how lockdown restrictions impacted individuals differently and who was more likely to change their exercise behavior and experience negative well-being. The current study examined exercise dependence as a risk factor and its impact on exercise behavior and mood during the initial COVID-19 lockdowns on a global scale in 11,898 participants from 17 countries. Mixed effects models revealed that reducing exercise behavior was associated with a stronger decrease in mood for individuals at risk of exercise dependence compared to individuals at low risk of exercise dependence. Participants at high risk and exercising more prior to the pandemic reported the most exercise during lockdown. Effects of lowered mood were most pronounced in participants with high risk of exercise dependence who reported greater reduction in exercise frequency during lockdown. These results support recent etiological evidence for exercise dependence and add to a growing body of literature documenting mental health effects related to COVID-19.
Public Significance Statement As we have entered an age of unprecedented mass displacement, global solutions are necessary. Participatory science offers an opportunity for a transformative shift toward equitable partnerships between researchers and communities toward innovation and may provide a key to unsolved problems, as well as tap into the possibilities for progress and growth. This special issue on participatory research with immigrant and refugee communities offers a roadmap for advancing the field of psychology.
Objectives:
The major global problems of our day, including mass displacement, climate change, violence, and pandemic, necessitate global solutions. In a world where injustice and inequities are rampant, psychologists stand at the precipice of social change and action, with an opportunity to unambiguously decolonize our research methodologies, and engage in scholarship that provides immediate benefits to communities.
Method:
Participatory methods offer an opportunity to co-create an empowering, equitable, inclusive, and ethical science in partnership with communities.
Results:
This special issue on Collaborative and Participatory Research to Promote Engagement, Empowerment, and Resilience for Immigrant and Refugee Youth, Families, and Communities highlights exemplary interdisciplinary work that has emerged in learning from and working in partnership with immigrant and refugee youth, families, and communities.
Conclusions:
The special issue offers six major components of participatory methodologies that provide a roadmap to decolonizing psychological science, recognize the potentials for innovation and impact, and advance the field.