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Saat ini, isu penggunaan energi yang berlebihan telah mewabah di masyarakat. Penggunaan energi yang berlebihan banyak ditemukan pada lingkungan rumah tangga. Penerapan rumah yang hemat energi dapat dijadikan solusi dalam mengatasi masalah tersebut. Namun, beberapa masyarakat tidak memprioritaskan konsep tersebut. Penelitian ini dimaksudkan untuk menentukan bagaimana persepsi masyarakat mengenai kepentingan menerapkan konsep rumah hemat energi pada rumah tinggal sehari – hari dan menentukan hal – hal yang perlu diperhatikan dalam menciptakan konsep rumah hemat energi. Metode pengumpulan data dilakukan melalui kuesioner ke beberapa responden lapisan masyarakat baik itu karyawan, wiraswasta, maupun mahasiswa. Data yang telah terkumpul dianalisis menggunakan analisis kualitatif data teks. Hasil dari analisis tersebut akan menghasilkan faktor – faktor yang menjadi alasan kepentingan menerapkan konsep rumah hemat energi dan kriteria dalam penerapan rumah hemat energi.

Gas hydrates are regarded as one of the most promising alternative sources of energy, which have the potential to address the energy demand of a contemporary society. Based on the field explorations in the Eastern Nankai Trough (Japan), a multilayered hydrate reservoir model has been conceptualised and its behaviours during depressurisation production are simulated. This model incorporates the effects of the initial reservoir temperature and permeability on the mechanism of hydrate dissociation, which in turn affects the gas production. It is shown that the dissociation process is largely affected by the initial temperature distribution within the reservoir layers, and the ‘warmer’ reservoirs show (consistently) higher production potential. Furthermore, the gas production could be improved significantly, by increasing the permeability of the wellbore region, which can be achieved through the fracturing process. The close match between the simulation results and the field tests is noteworthy. The proposed multilayered model would be quite useful for analysing the efficacy of the ‘production strategy’, in most real-life situations.

The impact of gas hydrate dissociation on submarine landslides has become an increasingly significant issue. However, previous models cannot interpret the newly discovered non-conformity between the slide surface and the base of the gas hydrate stability zone. Here, the authors design an experimental approach for visualising fluid migration during hydrate dissociation at atmospheric pressure. The results identify the lateral and vertical fluid migration pathways. Weak layers propagate nearly laterally beyond the hydrate zone, which lengthens the potential slide surface. Vertical pathways branch and deviate from their original paths, generating a shallower slide surface. Furthermore, the findings show that fluid overpressure under the overlying layer leads to steepening slopes. The lubrication effect and the underestimated inclination of slopes at failure may account for the low-angle failure of clay slopes. The results support a new conceptual model that reconciles the non-conformity between the slide surface and the base of the gas hydrate stability zone and offer a new perspective for the large-scale failure of low-angle submarine slopes. It will be interesting and important to confirm these implications in the future.

PurposeThis study aims to assess and decompose the sustainable development using the 17 sustainable development goals (SDGs) in Iran in 2018, for proposing agenda-setting of public policy.Design/methodology/approachIt ranks the SDGs not only in Iran but also in the region and the world to reveal the synergetic effects.FindingsBased on the results, subaltern-populace generally suffers from the hegemonic domination of ruling elite-bourgeois, lack of strong institutions, heterogeneous policy networks and lack of advocacy role of non-governmental organizations, due to no transparency, issues in law or no rule of law, no stringent regulation, rent, suppression and Mafia, all leading to corruption and injustice.Practical implicationsTo stop the loop of corruption-injustice, Iran should homogenize the structure of the policy network. Furthermore, the failed SDGs of the three-geographic analysis are the same in a character; all of them propose SDG 3, good health and well-being as a serious failed goal.Social implicationsIn this regard, strong evidence is the pandemic Coronavirus, COVID 19 since 2019, due to its highly-disastrous consequences in early 2020 where the public policymakers could not adopt policies promptly in the glob, particularly in Iran.Originality/valueIn Iran, in addition to this, the malfunction of health is rooted in “subjective well-being” and “traffic deaths,” respectively. Concerning the transportations system in Iran, it is underscored that it is damaging the sustainable development from all the three pillars of sustainable development including, economic, social and environmental.

This is the first work that incorporates recent advancements in "explainability" of machine learning (ML) to build a routing obfuscator called ObfusX. We adopt a recent metric---the SHAP value---which explains to what extent each layout feature can reveal each unknown connection for a recent ML-based split manufacturing attack model. The unique benefits of SHAP-based analysis include the ability to identify the best candidates for obfuscation, together with the dominant layout features which make them vulnerable. As a result, ObfusX can achieve better hit rate (97% lower) while perturbing significantly fewer nets when obfuscating using a via perturbation scheme, compared to prior work. When imposing the same wirelength limit using a wire lifting scheme, ObfusX performs significantly better in performance metrics (e.g., 2.4 times more reduction on average in percentage of netlist recovery).

Theories can be represented as statistical models for empirical testing. There is a vast literature on model selection and multimodel inference that focuses on how to assess which statistical model, and therefore which theory, best fits the available data. For example, given some data, one can compare models on various information criterion or other fit statistics. However, what these indices fail to capture is the full range of counterfactuals. That is, some models may fit the given data better not because they represent a more correct theory, but simply because these models have more fit propensity - a tendency to fit a wider range of data, even nonsensical data, better. Current approaches fall short in considering the principle of parsimony (Occam’s Razor), often equating it with the number of model parameters. Here we offer a toolkit for researchers to better study and understand parsimony through the fit propensity of Structural Equation Models. We provide an R package (ockhamSEM) built on the popular lavaan package. To illustrate the importance of evaluating fit propensity, we use ockhamSEM to investigate the factor structure of the Rosenberg Self-Esteem Scale.

The restoration of contaminated sites is attracting increasing attention because of environmental considerations. Barrier walls using cement-based solidified soil are a popular and effective method for enclosing contaminated sites. However, the working environment of cement-based solidified soils is often complicated and results in concern about the durability of the walls. Hence, the deterioration behaviour of solidified soils under a working environment should be investigated. A type of marine soft clay deposited in the coastal Lianyungang region of east China was solidified by a cement–metakaolin composite; then, the specimens were cured under standard, saline solution and cycled freeze–thaw environments. When the specimens reached the designed curing periods, the unconfined compressive strength, mass loss, pH value and mesostructure were determined. The results show that (a) both saline soaking and cycled freeze–thaw environments unavoidably reduce the durability of cement-based solidified soils and (b) metakaolin incorporation can effectively resist the deterioration behaviour of solidified soils under such environments. In this case, the optimal incorporation ratio is approximately 3·0%, and (c) although strength enhancement by chloride (Cl−) ions was primarily inhibited by the water medium, metakaolin incorporation suppresses cracking on the surface and strengthens the integrity of the solidified soils.

A study was carried out at CSIR-CIMAP, RC. Hyderabad (India) to study the impact of coppicing time on the oil percent and its chemical composition of different cultivars of lemongrass using a randomized block design. The freshly harvested herb was used for the hydro-distillation for essential oil, and subsequent chemical analysis. The chemical components identification of the essential oil was performed by GC–MS. In the results coppicing time influenced significant changes in the essential oil content, essential oil yield, and its chemical composition especially, total citral, and geraniol content. The four top rankers varieties/cultivars of lemongrass for the essential oil yield were CIM-Shikhar > Krishna > CKP-25 > CIMAP-Suwarna; for the essential oil content CIM–Shikhar > Krishna > CIMAP-Suwarna > Praman; for total citral content Nima > CIM–Shikhar > Krishna > Pragati, and for the total geraniol content Himrosa > CN-5 > Tawirosa > Kalam, respectively. Therefore, we can recommend these varieties/cultivars for commercial cultivation in large areas under the semi-arid region of south India.

In this paper, we propose and analyze SPARQ-SGD, an event-triggered and compressed algorithm for decentralized training of large-scale machine learning models over a graph. Each node can locally compute a condition (event) which triggers a communication where quantized and sparsified local model parameters are sent. In SPARQ-SGD, each node first takes a fixed number of local gradient steps and then checks if the model parameters have significantly changed compared to its last update; it communicates further compressed model parameters only when there is a significant change, as specified by a (design) criterion. We prove that SPARQ-SGD converges as $O\left( {\frac{1}{{nT}}} \right)$ and $O\left( {\frac{1}{{\sqrt {nT} }}} \right)$ in the strongly-convex and non-convex settings, respectively, demonstrating that aggressive compression, including event-triggered communication, model sparsification and quantization does not affect the overall convergence rate compared to uncompressed decentralized training; thereby theoretically yielding communication efficiency for ‘free’. We evaluate SPARQ-SGD over real datasets to demonstrate significant savings in communication bits over the state-of-the-art.

The disposal of metal plating sludge (PS) to landfills is an increasingly common practice in developed and developing countries. This paper presents a novel PS stabilisation technique using fly ash (FA)-based geopolymers as a waste management option. Strength and microstructural evaluations were carried out on PS-FA geopolymers at various values of factors, including liquid alkaline activator (L = sodium silicate (Na2SiO3)/sodium hydroxide (NaOH) ratio), L/FA ratios, FA/PS ratios and curing time. Increasing the amount of PS in PS-FA geopolymers reduced the total porosity, subsequently resulting in higher unconfined compressive strength (UCS) values. The main geopolymerisation product of the FA-based geopolymer was sodium aluminosilicate hydrate (N-A-S-H) gel. Since PS had a high calcium content, it would react with the high amount of silica and alumina present in FA to generate calcium aluminosilicate hydrate (C-A-S-H) gel in PS-FA geopolymers. This C-A-S-H gel coexisted with the N-A-S-H gel from FA-based geopolymers and hence significantly accelerated UCS development of PS-FA geopolymers over time. The UCS values of PS-FA geopolymers were found to meet the US Environmental Protection Agency requirement for disposal to landfills. The outcomes from this research can be translated into a regulatory framework for managing PS and diverting this industrial waste from landfills.

Supply chain collaborations may generate substantial cost savings. Many such initiatives cease to exist, however, due to not reaching an agreement on how to share the gains. We describe an exercise to understand the challenges in collaborative gain sharing. Funding: This project has received funding from the European Union’s Seventh Programme for research, technological development and demonstration (FP7 Transport) [Grant Agreement 284926].

We introduce a cross-entropy (CE) indicator to quantify the extent to which two input-output tables or two tables with results based on input-output analysis differ from each other. Our work deploys a unique feature of the CE indicator: it can be decomposed, allowing for matrix comparisons at various levels within one coherent framework. To illustrate the power of this approach, we apply the technique to five multi-region input-output (MRIO) tables for 2011, derived from the Eora, EXIOBASE, GTAP, OECD and WIOD databases. We make pairwise comparisons between MRIOs and between global value chain (GVC) computations based on these MRIOs. We find that answers to questions related to broader aggregates are generally quite similar, but that answers to questions at the level of single industries can be rather different across MRIOs.

Background Workplace absenteeism increases significantly during influenza epidemics. Sick leave records may facilitate more timely detection of influenza outbreaks, as trends in increased sick leave may precede alerts issued by sentinel surveillance systems by days or weeks. Sick leave data have not been comprehensively evaluated in comparison to traditional surveillance methods. The aim of this paper is to study the performance and the feasibility of using a detection system based on sick leave data to detect influenza outbreaks. Methods Sick leave records were extracted from private French health insurance data, covering on average 209,932 companies per year across a wide range of sizes and sectors. We used linear regression to estimate the weekly number of new sick leave spells between 2016 and 2017 in 12 French regions, adjusting for trend, seasonality and worker leaves on historical data from 2010 to 2015. Outbreaks were detected using a 95%-prediction interval. This method was compared to results from the French Sentinelles network, a gold-standard primary care surveillance system currently in place. Results Using sick leave data, we detected 92% of reported influenza outbreaks between 2016 and 2017, on average 5.88 weeks prior to outbreak peaks. Compared to the existing Sentinelles model, our method had high sensitivity (89%) and positive predictive value (86%), and detected outbreaks on average 2.5 weeks earlier. Conclusion Sick leave surveillance could be a sensitive, specific and timely tool for detection of influenza outbreaks.

An analytical procedure has been introduced to enable a study of the excretion of free bisphenol A (BPA), total BPA and its main metabolite bisphenol A glucuronide (BPA-GLUC). In the experiment, in which 100 μg/kg b. w. BPA was administered daily to one Istrian Pramenka sheep for 5 days with consecutive urine and feces samples being taken, BPA and total BPA were determined in samples using high-performance liquid chromatography (HPLC) with fluorescence detection. Because of their good recovery, precision, and sensitivity, the methods have also proved applicable to further ecotoxicological studies of free BPA, BPA-GLUC and total BPA. The results were subsequently compared with reported field studies of BPA in livestock excreta.

Given that cultivated land serves as a strategic resource to ensure national food security, blind emphasis on improvement of food production capacity can lead to soil overutilization and impair other soil functions. Therefore, we took Heilongjiang province as an example to conduct a multi-functional evaluation of soil at the provincial scale. A combination of soil, climate, topography, land use, and remote sensing data were used to evaluate the functions of primary productivity, provision and cycling of nutrients, provision of functional and intrinsic biodiversity, water purification and regulation, and carbon sequestration and regulation of cultivated land in 2018. We designed a soil function discriminant matrix, constructed the supply-demand ratio, and evaluated the current status of supply and demand of soil functions. Soil functions demonstrated a distribution pattern of high grade in the northeast and low grade in the southwest, mostly in second-level areas. The actual supply of primary productivity functions in 71.32% of the region cannot meet the current needs of the population. The dominant function of soil in 34.89% of the area is water purification and regulation, and most of the cultivated land belongs to the functional balance region. The results presented herein provide a theoretical basis for optimization of land patterns and improvement of cultivated land use management on a large scale, and is of great significance to the sustainable use of black soil resources and improvement of comprehensive benefits.

Polybrominated diphenyl ethers (PBDEs) have widely been used for decades as flame retardants in a variety of products like plastics for building insulation, upholstered furniture, electrical appliances, vehicles, aircrafts, polyurethane foams, textiles, cable insulation, appliance plugs and various technical plastics in concentrations of 5-30%. However, PBDEs also act as endocrine disrupters, neurotoxins, and negatively affect fertility. In 2001, worldwide consumption of technically relevant penta-BDEs was still estimated at 7500 tons, octa-BDEs at 3790 tons, and deca-BDE at 56,100 tons, but 50-60% of this total volume are discharged into the environment via sewage sludge and its agricultural use alone. In addition, soils are ubiquitously contaminated by the gaseous or particle-bound transport of PBDEs, which today has its main source in highly contaminated electronic waste recycling sites. The emitted PBDEs enter the food chain via uptake by the plants’ roots and shoots. However, uptake and intrinsic transport behaviour strongly depend on crop specifics and various soil parameters. The relevant exposure and transformation pathways, transport-relevant soil and plant characteristics and both root concentration factors (RCF) and transfer factors (TF) as derivable parameters are addressed and quantified in this review. Finally, a simple predictive model for quantification of RCF and TF based on log KOW values and the organic content of the soil/lipid content of the plants is also presented., Umweltbundesamt, Projekt DEAL

This paper was initiated in order to find the usage and relevance of the Information and Communication Technologies (ICT) by the smallholder farmers of the Umzimvubu Local Municipality of the Eastern Cape Province in South Africa. A survey questionnaire was then developed to collect the relevant data from randomly selected six villages of Umzimvubu Local Municipality targeting 138 respondents. The questionnaires structure employed both closed and open-ended questions that were administered using a face to face interview, conducted on the sample population in each village. There seems to be a correlation between ICT usage and the economies of scale in agricultural development, where smallholder farmers tend to use less of highly modernized ICT, while commercial large scale farmers use more of the modernized ICT. This disparity amongst farmers is exacerbated in many areas by the differing support systems employed by the public extension services.

In the autonomous ocean monitoring task, the sampling robot moves in the environment and accumulates data continuously. The widely adopted spatial modeling method - standard Gaussian process (GP) regression - becomes inadequate in processing the growing sensing data of a large size. To overcome the computational challenge, this paper presents an environmental modeling framework using a sparse variant of GP called streaming sparse GP (SSGP). The SSGP is able to handle streaming data in an online and incremental manner, and is therefore suitable for long-term autonomous environmental monitoring. The SSGP summarizes the collected data using a small set of pseudo data points that best represent the whole dataset, and updates the hyperparameters and pseudo point locations in a streaming fashion, leading to high-quality approximation of the underlying environmental model with significantly reduced computational cost and memory demand., Proceedings of OCEANS 2019, SEATTLE

A total of 11 bacterial strains capable of completely degrading 2-butoxyethanol (2-BE) were isolated from forest soil, a biotrickling filter, a bioscrubber, and activated sludge, and identified by 16S rRNA gene sequence analysis. Eight of these strains belong to the genus Pseudomonas; the remaining three strains are Hydrogenophaga pseudoflava BOE3, Gordonia terrae BOE5, and Cupriavidus oxalaticus BOE300. In addition to 2-BE, all isolated strains were able to grow on 2-ethoxyethanol and 2-propoxyethanol, ethanol, n-hexanol, ethyl acetate, 2-butoxyacetic acid (2-BAA), glyoxylic acid, and n-butanol. Apart from the only gram-positive strain isolated, BOE5, none of the strains were able to grow on the nonpolar ethers diethyl ether, di-n-butyl ether, n-butyl vinyl ether, and dibenzyl ether, as well as on 1-butoxy-2-propanol. Strains H. pseudoflava BOE3 and two of the isolated pseudomonads, Pseudomonas putida BOE100 and P. vancouverensis BOE200, were studied in more detail. The maximum growth rates of strains BOE3, BOE100, and BOE200 at 30 °C were 0.204 h-1 at 4 mM, 0.645 h-1 at 5 mM, and 0.395 h-1 at 6 mM 2-BE, respectively. 2-BAA, n-butanol, and butanoic acid were detected as potential metabolites during the degradation of 2-BE. These findings indicate that the degradation of 2-BE by the isolated gram-negative strains proceeds via oxidation to 2-BAA with subsequent cleavage of the ether bond yielding glyoxylate and n-butanol. Since Gordonia terrae BOE5 was the only strain able to degrade nonpolar ethers like diethyl ether, the degradation pathway of 2-BE may be different for this strain., Projekt DEAL, Landesgraduiertenförderung der Universität Stuttgart

Many proponents of organic farming claim that it is a sustainable alternative to conventional agriculture due to its reliance on natural agro-inputs, such as manure based fertilizers and organic pesticides. However, in this analysis we argue that although particular organic farming practices clearly benefit ecosystems and human consumers, the social context in which some organic farms develop, limit the potential environmental benefits of organic agriculture. Specifically, we argue that certified organic farming’s increased reliance on agro-inputs, such as organic fertilizers and pesticides, reduces its ability to decrease global water pollution. We review recent research that demonstrates the environmental consequences of specific organic practices, as well as literature showing that global organic farming is increasing its reliance on agro-inputs, and contend that organic farming has its own metabolic rift with natural water systems similar to conventional agriculture. We use a fixed-effects panel regression model to explore how recent rises in certified organic farmland correlate to water pollution (measured as biochemical oxygen demand). Our findings indicate that increases in the proportion of organic farmland over time increases water pollution. We conclude that this may be a result of organic farms increasing their reliance on non-farm agro-inputs, such as fertilizers.

International audience; Ozone, PM10 and PM2.5 concentrations over Paris, France and Stockholm, Sweden were modeled at 4 and 1 \unit{km} horizontal resolutions respectively for the present and 2050 periods employing decade-long simulations. We account for large-scale global climate change (RCP-4.5) and fine resolution bottom-up emission projections developed by local experts and quantify their impact on future pollutant concentrations. Moreover, we identify biases related to the implementation of regional scale emission projections over the study areas by comparing modeled pollutant concentrations between the fine and coarse scale simulations. We show that over urban areas with major regional contribution (e.g., the city of Stockholm) the bias due to coarse emission inventory may be significant and lead to policy misclassification. Our results stress the need to better understand the mechanism of bias propagation across the modeling scales in order to design more successful local-scale strategies. We find that the impact of climate change is spatially homogeneous in both regions, implying strong regional influence. The climate benefit for ozone (daily average and maximum) is up to -5 % for Paris and -2 % for Stockholm city. The joined climate benefit on PM2.5 and PM10 in Paris is between -10 and -5 % while for Stockholm we observe mixed trends up to 3 % depending on season and size class. In Stockholm, emission mitigation leads to concentration reductions up to 15 % for daily average and maximum ozone and 20 % for PM and through a sensitivity analysis we show that this response is entirely due to changes in emissions at the regional scale. On the contrary, over the city of Paris (VOC-limited photochemical regime), local mitigation of NOx emissions increases future ozone concentrations due to ozone titration inhibition. This competing trend between the respective roles of emission and climate change, results in an increase in 2050 daily average ozone by 2.5 % in Paris. Climate and not emission change appears to be the most influential factor for maximum ozone concentration over the city of Paris, which may be particularly interesting in a health impact perspective.

Advanced transportation biofuels have been the focus of intensive development since the early 2000s, and gasification in combination with synthesis technologies represents a flexible production pathway to deliver fuels for heavy-duty transport sectors that are difficult to electrify. This article is related to the pilot-scale development of a process concept aiming to smaller-scale production plants than are feasible with fluidized-bed gasifiers. Five test weeks with a total gasification time of 347 hours were realized at a pilot plant that consisted of the pressurized staged fixed-bed gasifier, raw gas cooling to 500–600 °C, filtration with robust metal filters, and catalytic reforming of tars and methane. The gasifier combined an updraft primary stage and a catalytically enhanced secondary stage where most of the updraft tars were decomposed. The tar content of the product gas, 2–12 g/m3, was of the same order of magnitude as determined previously for fluidized-bed gasifiers. Consequently, similar filtration and reforming methods could be successfully applied. After the reformer, the contents of C2-hydrocarbon gases and high-molecular-weight tars were negligible. Esa Kurkela,* Minna Kurkela, Ilkka Hiltunen Pilot-scale development of pressurized fixed-bed gasification for synthesis gas production from biomass residues Biomass Conversion and Biorefinery https://doi.org/10.1007/s13399-021-01554-2

Co-production in climate change has arisen in response to improving climate knowledge. Climate service co-production provides climate knowledge for decision-making, benefiting vulnerable communities with useful and usable information such as flooding risk areas. A climate service co-production project, including mapping technologies, has been conducted in Jakarta, Indonesia. However, it has not been integrated into mainstream spatial planning. This paper investigates an enabling environment for the integration of climate service co-production and spatial planning using a collaborative governance framework. We conducted semi-structured interviews, photovoice, and focus group discussions. The results highlight factors to enable integration; (1) an institutional reform to put climate service co-production on the agenda, (2) top-down priorities aligned with local-level needs, (3) local government will and leadership to execute the tasks and actions towards climate resilience, (4) trust of the local government with the community, (5) integrated geospatial data to have an effective climate knowledge to spatial planning.

A study was conducted to evaluate the efficacy of recycled concrete aggregate (RCA) and off-specification fly ash (FA) in remediating acid mine drainage (AMD). The pH and AMD concentrations of calcium (Ca), magnesium (Mg), iron (Fe), chromium (Cr), copper (Cu), manganese (Mn) and zinc (Zn) were assessed. The effects of RCA particle size on pH and AMD metal concentrations were also investigated. Results showed that RCAs were effective in neutralising the acidic pH and lowering the AMD concentrations of iron, chromium, copper and zinc. The concentrations of calcium increased, but magnesium and manganese concentrations varied in the treatment process. FA acted as an additional source of metals and increased the concentrations of iron, copper and manganese significantly. Finer RCA particles were the most effective in raising the pH and reducing the AMD concentrations of magnesium, manganese and zinc. The concentrations of calcium, iron, chromium and copper remained unaffected by the RCA particle size. In addition, geochemical modelling indicated that sorption was the leaching controlling mechanism in untreated and FA-treated AMD, whereas it was solubility-controlled leaching in RCA-treated AMD. Finally, the research reported in this study suggests the use of RCA as an effective alternative to the conventional treatment methods for AMD remediation.

International audience; Using an approach that embodies an explicit tradeoff between need and governance considerations, we propose an optimal aid allocation formula. We first assume exogenous, then endogenous governance. In the former case, a central concept is need-adjusted aid effectiveness while in the second case the donor has policing instruments under the form of monitoring and sanctioning capacities. We show that external disciplining has two advantages when the donor is sensitive enough to poverty intensity: (1) to cater to poor countries to a greater extent than is possible when local governance cannot be influenced by external forces, and (2) to respond (non-perversely) to improvements in the local governance of a country by raising its aid share. In institutionally weak countries, populations should welcome wisely applied donor's discipline as a way not only to get access to financial support but also to constrain their elites to refrain from abusing their position excessively. Imposing discipline when the release of externally-provided development funds is at stake seems more acceptable than aid directed to the explicit purpose of combatting corruption.

Urban expansions into natural habitats have forced many carnivores to adapt to the modified areas; however, our understanding of their ecology in such areas is limited. The Indian fox (Vulpes bengalensis) is a small carnivore species that can adapt and exploit urban areas due to its generalist nature, but there is a paucity of data on Indian foxes in these human-modified areas. To understand the resource requirement of Indian foxes in urban habitats, we conducted a diet analysis by examining 119 scats of Indian foxes in a peri-urban habitat of Baripada town, Odisha, eastern India. To determine the diet composition of Indian foxes, we analyzed scat contents by their frequency occurrence (%FO), the relative frequency of occurrence (%RF) and mean percent volume (%Vm). Indian foxes consumed a wide range of food categories, including arthropods, rodents, reptiles, birds, plant parts and anthropogenic resources. In %Vm, rodents showed the highest volume, followed by polythene, Spondias pinnata fruit and Coleoptera. We found anthropogenic foods in considerable quantities, including polythene and paper. The diet of Indian foxes indicates that the species has opportunistic and generalist feeding habits consisting primarily of easily accessible foods. Furthermore, management efforts should focus on the proper management of waste and control of anthropogenic food sources in urban habitats.

Plants sustain several ecosystem functions thereby playing a crucial role in conservation management. Lantana camara an invasive weed has become the common part of a bushes. The mutualistic relationship between this weed plant and butterflies are well known. Butterflies depend on Lantana camara for food, oviposition site, larval development etc. In this context we are highlighting the role of this invasive weed for butterfly conservation and maintaining total butterfly abundance. In this study the species richness highest for the site where the bushes were dominated by Lantana camara and lowest for the site where LCA abundance was low. The butterfly abundance and LCA abundance maintain a strong positive relationship and LCA abundance, species richness and and butterfly abundance are strongly correlated and dominance is negatively correlated with other three variables. So we can use the Lantana camara as a model organism for conservation and maintaining the butterfly abundance in Purulia, West Bengal, India.

Roselle (Hibiscus sabdariffa L.) is recognized as a valuable food crop due to its nutraceutical potential, rich pigment content, and medicinal properties. However, there is limited information on planting dates and suitable genotypes for roselle cultivation in arid and semi-arid regions. The objective of this field study was to investigate the influence of five planting dates (March, April, May, June, and July) on morphological and phytochemical characteristics of different roselle genotypes. Among genotypes, eight (Jiroft, Dalgan, Bampoor, Iranshahr, Nikshahr, Roodbar, Saravan, and Qaleganj) were Iranian landraces, and HA and HS-24 were originated from Ghana and Bangladesh, respectively. Planting date significantly influenced the number of branches, bolls and seeds per plant, sepal fresh weight, calyx and biomass yields, and harvest index in tested roselle landraces. The greatest morphological growth, fresh sepal weight (50.6 g plant−1) and calyx yield (1519 kg ha−1) were observed with the roselle planted in early May. Moreover, amounts of chlorophyll, flavonoids and antioxidant remained higher in roselle when planted between April–May. The number of branches/plant was found to be an important determinant of calyx yield (r = 0.707) in roselle. Dalgan resulted in the greatest growth and yields within a comparatively shorter period of time compared to other tested landraces. Both principal component analysis (PCA) and cluster analysis also indicated that Dalgan landrace possessed most suitable morphological and phytochemical traits among tested landraces, and therefore, it could be planted adopted for extensive cultivation settings in the arid and semi-arid regions.

Bacteria are considered as foremost bioremediating agents among microorganisms, encompassing simple biological mechanism to tolerate higher concentration of heavy metal and favoring conservative strategies to substitute the usage of chemicals. Relating this implication, the present study is designed to identify, screen and characterize bacteria from industrial site soil to tolerate multimetals. Almost 108 colonies were obtained at various concentrations (0.5–2.0 mM) of heavy metals (cadmium, nickel and lead) and were thrived in the reformed minimal media. Bacterial isolates that grown in the higher concentration of heavy metals (2.0 mM) were taken for further studies. Among ten bacterial colonies, one isolate was selected for each heavy metal and further screened for their multi metal tolerance. Isolate, C20 alone survived in heavy metal mixture fortified medium with high recovery rate and increased colony forming units. Molecular level characterization and phylogenetic tree analysis revealed that the isolate is identical to Bacillus thuringiensis. The study highlights that the multi metal tolerant B. thuringiensis could be used as an effective bioremediating agent to manage heavy metals particularly cadmium, nickel and lead in industrial area. Further, attributed to be a plant growth promoting rhizobacteria, this organism can promote dual stratagems as a bio remediating agent and fertility enhancer in agricultural field due to its dual functions.

Contextual information, such as the co-occurrence of objects and the spatial and relative size among objects, provides rich and complex information about digital scenes. It also plays an important role in improving object detection and determining out-of-context objects. In this work, we present contextual models that leverage contextual information (16 contextual relationships are applied in this paper) to enhance the performance of two of the state-of-the-art object detectors (i.e., Faster RCNN and YOLO), which are applied as a post-processing process for most of the existing detectors, especially for refining the confidences and associated categorical labels, without refining bounding boxes. We experimentally demonstrate that our models lead to enhancement in detection performance using the most common dataset used in this field (MSCOCO), where in some experiments PASCAL2012 is also used.We also show that iterating the process of applying our contextual models also enhances the detection performance further.

Years of community-driven research and participatory action have shed an important light on the copious negative health issues burdening communities adjacent to industrial agriculture. Rural commun...

Canola meal is a low-value agricultural residue obtained after oil extraction from canola, the utilization of which requires further attention. On the other hand, plastic waste disposal is also another leading issue that creates severe environmental challenges. Supercritical water gasification is considered an environmentally friendly technology to produce hydrogen from plastic residues and organic wastes. This study deals with hydrothermal co-gasification of canola meal and plastic wastes (i.e., low-density polyethylene) while exploring the influence of temperature (375–525°C), residence time (15–60 min) and plastic-to-biomass ratio (0:100, 20:80, 50:50, 80:20 and 100:0) on hydrogen yield. Maximum hydrogen yield (8.1 mmol/g) and total gas yield (17.9 mmol/g) were obtained at optimal temperature and residence time of 525°C and 60 min, respectively. A change in the gas yield with variable plastic-to-biomass ratio showed synergistic effects between both feedstocks. The trend of catalytic performance towards improving hydrogen yield was in the following order: WO3–TiO2 (18.5 mmol/g) > KOH (16.9 mmol/g) > TiO2 (9.5 mmol/g) > ZrO2 (7.8 mmol/g) > WO3–ZrO2 (7.4 mmol/g).

New indigenous bacteria, extracted from soil samples that had been collected from different parts of Iran, were introduced to improve dune sand using microbially induced carbonate precipitation (MICP) as an environmental engineering method. In order to isolate urease-producing bacteria from local alkaline soils, a series of standard tests was conducted to evaluate the urease performance and potential of calcium carbonate (calcite) sedimentation. Based on their properties, the bacteria with the best performance were identified by 16S ribosomal ribonucleic acid sequencing. To achieve a better understanding of the performance of the selected isolates, Sporosarcina pasteurii was employed as the control sample. The geotechnical behaviour of bio-mediated sand was studied through a series of geotechnical experiments, including unconfined compressive strength (UCS), constant-head permeability and wind erosion tests. The influence of freeze–thaw cycles and the durability of specimens on the UCS was also investigated. It is worth noting that sand MICP-treated by Bacillus sp. UTMC 2623 gave a performance relatively equal to that of the control sample during all UCS tests. Scanning electron microscopy images and X-ray diffraction were also used to observe calcite precipitation formation using Bacillus sp. UTMC 2623, which indicated precipitation of calcite throughout the sand column.

Enormous biotic stresses, such as uncontrolled grazing, logging, use of plants for timber and fuelwood, deforestation for cultivation, and road constructions have drastically deteriorated forests in the Kashmir Himalaya. On the basis of the intensity of biotic stress, three differently forest sites, protected, unprotected and roadside forest, were studied. Random vegetation sampling was done to record herbaceous diversity in the Tangmarg Forest Division of Kashmir valley in 2019. Six diversity indices were negatively correlated with increasing levels of anthropogenic disturbance. The values further elucidated by the Renyi diversity profiles, indicated that the protected forest sites had significantly higher diversity as compared to the road side forest sites. Scaling based on an increased order of total number of species in the forest richness and diversity – on top were protected forest sites, followed by unprotected forest sites, while road side forest sites were on the lower end of this spectrum. The Principal component analysis (PCA) showed two distinct groups based on the composition and IVI of the plant species. The results of this study identify diverse biotic stresses and could help in framing the policies for forest management.

Clove basil (Ocimum gratissimum L.) is an aromatic, perennial herb belonging to the family Lamiaceae. The plant is indigenous to tropical areas especially India and West Africa. In Nigeria, it is found in the Savannah and coastal areas. The whole herbs of the plant contain essential oils and it is cultivated for various purposes. The plant is a rich source of eugenol in its essential oil. It is also used in the preparation of tea and infusions. It is also used in the treatment of fungal infections, fever, cold, and cough. Eugenol (4-allyl-2-methoxy phenol) is a phenolic compound from the class of phenylpropanoids. It is used in the food industry as a preservative, mainly due to its antioxidant property, and flavoring agent. The fresh herb × winter season/environment produced the highest essential oil 2.07 mL/plot with essential oil content 0.41% followed by fresh herb × summer season/environment (M1S2) = 1.68 mL. For the eugenol content, the autumn season/environment was found highly favorable = 74.52% (leaves = 69.024, stem = 74.531, and in inflorescence = 80.012) followed winter season/environment 72.30% (leaves = 71.841, stem 69.389, inflorescence 76.042, mean = 72.42%). These seasons are recommended for harvesting to obtain the optimum benefit for the quality essential oil yield.

Desiccation cracks in clay play an important role in many geoenvironmental applications such as clay liners in engineered landfills, preferential flows and contaminant transport. In this study, a comprehensive series of experiments was conducted to investigate the desiccation cracks due to the combined effects of initial water content and layer thickness on bentonite clay. Slurries of bentonite were prepared with initial water contents ranging from 1200 to 2200%. The slurry was placed in a glass Petri dish and dried at a temperature of 30 ± 2°C. Results from the experiments were illustrated in a phase diagram, and it was found that the interplay between the initial water content and layer thickness has a significant effect on the formation and prevention of desiccation cracks. More specifically, a phase boundary distinguishing between cracked and non-cracked samples was obtained in the constructed phase diagram. A theoretical model based on the critical cracking thickness was developed and then was used to predict this observed phase boundary. Furthermore, a detailed morphology of crack patterns was investigated by employing image analysis techniques followed by statistical analyses. Findings from this study have potential use in clay liner design, where bentonite is used as the main material, as well as in other problems associated with drying soils.

The species Schleichera oleosa (Kusum), being rich in nutritional, medicinal and processing qualities can play a very important role in the livelihood security of the rural communities through enhanced household income, employment generation and environmental protection. People of many states of India are becoming increasingly aware about the potential importance of this species in terms of its ethnobotany and lac production in their livelihood security. Value addition of all the components especially seed oil for biodiesel production, lac production and processing of bark for exploiting their nutritional and medicinal properties is a long-term strategy. There is need of increasing the area and plantation of this valuable species and enhancing their processed products. Moreover, to domesticate this species on farmer's field, there is a need to develop good cultivars. Hence, there is an ample scope in developing propagation methods and suitable good cultivars through nursery management programme. Dissemination of improved production technologies, value addition and marketing strategies regarding Kusum trees and its products to the farmers/entrepreneurs/lac based industries is of utmost importance for promoting it as agribusiness.

Spirulina is a filamentous, multi-cellular and autotrophic cyanobacterium having distinct features of helical shape filaments (i.e. trichomes). An investigation is to isolate a marine, Spirulina subsalsa from Vellar estuary, South East Coast zone of India. The isolated strain sub-cultured in Zarrouk medium with optimum conditions for sustaining growth. Pure cultures were examined in a research microscope for morphometric studies through 16S rRNA sequencing and the sequence was submitted to NCBI-GENBANK, the accession number is MW037197 which displays the maximum similarity as 100% with a diverse sequence in databank i.e. LC 215280. The investigation is the first record for the existence of Spirulina subsalsa in Vellar Estuary, South East Coast, Tamil Nadu (India) as affirmed by a molecular nucleotide sequence.

We consider Bandits with Knapsacks (henceforth, BwK), a general model for multi-armed bandits under supply/budget constraints. In particular, a bandit algorithm needs to solve a well-known knapsack problem: find an optimal packing of items into a limited-size knapsack. The BwK problem is a common generalization of numerous motivating examples, which range from dynamic pricing to repeated auctions to dynamic ad allocation to network routing and scheduling. While the prior work on BwK focused on the stochastic version, we pioneer the other extreme in which the outcomes can be chosen adversarially. This is a considerably harder problem, compared to both the stochastic version and the "classic" adversarial bandits, in that regret minimization is no longer feasible. Instead, the objective is to minimize the competitive ratio: the ratio of the benchmark reward to the algorithm's reward. We design an algorithm with competitive ratio O(log T) relative to the best fixed distribution over actions, where T is the time horizon; we also prove a matching lower bound. The key conceptual contribution is a new perspective on the stochastic version of the problem. We suggest a new algorithm for the stochastic version, which builds on the framework of regret minimization in repeated games and admits a substantially simpler analysis compared to prior work. We then analyze this algorithm for the adversarial version and use it as a subroutine to solve the latter., The extended abstract appeared in FOCS 2019. The definitive version was published in JACM '22. V8 is the latest version with all technical changes. Subsequent versions fixes minor LATEX presentation issues

Cyber-Physical Systems (CPS) connected in the form of Internet of Things (IoT) are vulnerable to various security threats, due to the infrastructure-less deployment of IoT devices. Device-to-Device (D2D) authentication of these networks ensures the integrity, authenticity, and confidentiality of information in the deployed area. The literature suggests different approaches to address security issues in CPS technologies. However, they are mostly based on centralized techniques or specific system deployments with higher cost of computation and communication. It is therefore necessary to develop an effective scheme that can resolve the security problems in CPS technologies of IoT devices. In this paper, a lightweight Hash-MAC-DSDV (Hash Media Access Control Destination Sequence Distance Vector) routing scheme is proposed to resolve authentication issues in CPS technologies, connected in the form of IoT networks. For this purpose, a CPS of IoT devices (multi-WSNs) is developed from the local-chain and public chain, respectively. The proposed scheme ensures D2D authentication by the Hash-MAC-DSDV mutual scheme, where the MAC addresses of individual devices are registered in the first phase and advertised in the network in the second phase. The proposed scheme allows legitimate devices to modify their routing table and unicast the one-way hash authentication mechanism to transfer their captured data from source towards the destination. Our evaluation results demonstrate that Hash-MAC-DSDV outweighs the existing schemes in terms of attack detection, energy consumption and communication metrics.

Funding Information: This research has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement (EnergyMatching project number 768766), and J. Gust. Richert foundation in Sweden (grant number: 2020-00586). Funding Information: This research has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement (EnergyMatching project number 768766 ), and J. Gust. Richert foundation in Sweden (grant number: 2020-00586 ). Publisher Copyright: © 2021 The Author(s) Peer-to-peer (P2P) energy sharing among neighboring households is a promising solution to mitigating the difficulties of renewable power (such as solar Photovoltaics (PV)) penetration on the power grid. Until now, there is still a lack of study on the impacts of future climate change on the P2P energy trading performances. The future climate change will cause variances in the renewable energy production and further lead to changes in the economic performances of households with various energy uses and affect the decision making in PV ownership and pricing strategies. Being unaware of these impacts could potentially hinder the P2P energy sharing application in practice. To bridge such knowledge gap, this paper conducts a systematic investigation of the climate change impacts on the energy sharing performance in solar PV power shared communities. The future weather data is generated using the Morphine method, and an agent-based modeling method is used for simulating the energy trading behaviors of households. Four comparative scenarios of different PV ownerships and pricing strategies are designed. The detailed energy trading performances (including the PV power self-sufficiency, cost saving, revenues, and compound annual growth rate) for the four comparative scenarios are analyzed under both the present and future climates and compared. The study results of a building community located in Sweden show that the future climate change is more beneficial to large energy use households while less beneficial to small households. High price of energy trading can improve the fairness of the economic performances in the community, especially when some of the households do not have any PV ownership. This study can help understand the future climate impacts on the energy sharing performances of building communities, which can in turn guide decision making in PV ownership and price setting for different households under the future climate change to facilitate real applications.

Spatial downsampling layers are favored in convolutional neural networks (CNNs) to downscale feature maps for larger receptive fields and less memory consumption. However, for discriminative tasks, there is a possibility that these layers lose the discriminative details due to improper pooling strategies, which could hinder the learning process and eventually result in suboptimal models. In this paper, we present a unified framework over the existing downsampling layers (e.g., average pooling, max pooling, and strided convolution) from a local importance view. In this framework, we analyze the issues of these widely-used pooling layers and figure out the criteria for designing an effective downsampling layer. According to this analysis, we propose a conceptually simple, general, and effective pooling layer based on local importance modeling, termed as {\em Local Importance-based Pooling} (LIP). LIP can automatically enhance discriminative features during the downsampling procedure by learning adaptive importance weights based on inputs. Experiment results show that LIP consistently yields notable gains with different depths and different architectures on ImageNet classification. In the challenging MS COCO dataset, detectors with our LIP-ResNets as backbones obtain a consistent improvement ($\ge 1.4\%$) over the vanilla ResNets, and especially achieve the current state-of-the-art performance in detecting small objects under the single-scale testing scheme., Comment: ICCV 2019 camera ready version. Code: https://github.com/sebgao/LIP

In social networks, one of the most significant challenges is how to estimate the tweet popularity. Prior studies focus on leveraging different aspects of just a single tweet, while ignoring the impact of historical tweets. In this paper, we propose to leverage such historical information and rethink the problem of tweet popularity estimation. From historical information, there are two important factors that can be extracted: (1) user reputation feature, which can represent coarse-grained level of tweet popularity; (2) tweet related features, which can represent fine-grained level of tweet popularity. To incorporate these two factors from historical information, we design a novel deep neural architecture, a Bi-layered LSTM for tweet popUlarity Estimation, called DeepBlue. Specifically, we first propose a user-reputation aware mechanism to combine coarse-grained and fine-grained level estimation into a united LSTM model. We also design a content attention mechanism to consider different impacts of historical tweets in terms of content similarity. We then propose a time aware mechanism to address the time interval irregularity issue. Finally, we apply the Poisson regression model to obtain the overall loss for tweet popularity estimation. Extensive experiments demonstrate the superiority of our proposed approach to other state-of-the-arts in terms of MAE and SRC.

Background: This research investigated and identified significant spatial clusters of asthma and chronic obstructive pulmonary disease (COPD)-related emergency department (ED) visits and in-patient...

The development of electric vehicle (EV) techniques has led to a new vehicle routing problem (VRP) called the capacitated EV routing problem (CEVRP). Because of the limited number of charging stations and the limited cruising range of EVs, not only the service order of customers but also the recharging schedules of EVs should be considered. However, solving these two aspects of the problem together is very difficult. To address the above issue, we treat CEVRP as a bilevel optimization problem and propose a novel bilevel ant colony optimization algorithm in this article, which divides CEVRP into two levels of subproblem: 1) capacitated VRP and 2) fixed route vehicle charging problem. For the upper level subproblem, the electricity constraint is ignored and an order-first split-second max-min ant system algorithm is designed to generate routes that fulfill the demands of customers. For the lower level subproblem, a new effective heuristic is designed to decide the charging schedule in the generated routes to satisfy the electricity constraint. The objective values of the resultant solutions are used to update the pheromone information for the ant system algorithm in the upper level. Through good orchestration of the two components, the proposed algorithm can significantly outperform state-of-the-art algorithms on a wide range of benchmark instances.

Lead (Pb) is one of the most paradoxical elements, both having diverse practical uses, as well as being extremely toxic to humans, and especially to children. The use of Pb records a steady growth with annual production currently exceeding 10 million metric tons. In spite of the environmental awareness of modern society, humans are still exposed to Pb through its emission by smelting and mining activities, and also by Pb-bearing mine wastes and soils. Here, we review the chemical and mineralogical forms of Pb generated from smelting and mining processes and subsequently altered in tailings, slag piles, and soils. In smelter plumes, Pb is emitted to the atmosphere either in the form of smaller nano-size particulate matter (PM) often associated with S, or larger micrometer Pb-bearing PM matter accompanied by oxide-silicate matrices. Pb-bearing phases in mine tailings and impacted soils depict a greater mineralogical and chemical complexity than those emitted from smelters and the larger particle size of this PM also leads to a lower Pb bioavailability. High resolution observations in aquatic system, soils and rock coatings impacted by smelting and mining activities show the presence of Pb-bearing phosphates, sulfides, sulfates, carbonates, and oxide nanoparticles. Larger micrometer size particles of Pb-bearing minerals form often through the aggregation of Pb-bearing nanoparticles, a process commonly referred to as crystallization through particle attachment. Mobilization of Pb within soil columns is strongly affected by the transport of colloids, especially those composed of organic matter and Fe-hydroxides because Pb is taken up efficiently by these two soil components. The extraordinary variability and complexities of all of these processes suggest that future reduction of Pb contamination in the environment and its impact on human health mainly depends on eliminating or greatly reducing Pb-release from smelting operations and tailings impoundments.

Smart passenger-seeking strategies employed by taxi drivers contribute not only to drivers’ incomes, but also higher quality of service passengers received. Therefore, understanding taxi drivers’ behaviors and learning the good passenger-seeking strategies are crucial to boost taxi drivers’ well-being and public transportation quality of service. However, we observe that drivers’ preferences of choosing which area to find the next passenger are diverse and dynamic across locations and drivers. It is hard to learn the location-dependent preferences given the partial data (i.e., an individual driver's trajectory may not cover all locations). In this paper, we make the first attempt to develop conditional generative adversarial imitation learning (cGAIL) model, as a unifying collective inverse reinforcement learning framework that learns the driver's decision-making preferences and policies by transferring knowledge across taxi driver agents and across locations. Our evaluation results on three months of taxi GPS trajectory data in Shenzhen, China, demonstrate that the driver's preferences and policies learned from cGAIL are on average 34.7% more accurate than those learned from other state-of-the-art baseline approaches.

This article analyses the concept of sufficiency in relation to sustainability and discusses ethical implications for sustainable organisation in time and place. We identify three foundational conceptualisations of sufficiency related to sustainability: (1) a limits model that starts with objective boundaries imposed by the biosphere and basic human needs; (2) a preference model that treats sufficiency as a subjective inclination for moderation defined situationally; and (3) a balancing model that seeks to integrate the objective limits and subjective preferences by focussing on action embedded in the socio-ecological context. This includes balancing the needs of humans with those of non-humans. The limits model builds on universal duty, the preference model on preference utilitarianism and the balancing model on action-oriented virtue ethics. The balancing model of sufficiency is well suited to meeting the needs of present and future generations as well as delivering intra- and inter-generational justice not limited to humans.

Human activities have significantly accelerated emissions of each carbon dioxide and biologically reactive nitrogen into the atmosphere. As nitrogen availability frequently limits forest productivity, it has long been anticipated that anthropogenic nitrogen deposition ought to stimulate carbon sequestration in forests. The present study aimed to understand the effects of nitrogen addition on the growth of the Syzygium cumini in ambient (408 ppm) and elevated (450 ppm, 500 ppm, 550 ppm and 600 ppm) carbon dioxide conditions. The addition of nitrogen in the form of potassium nitrate in different levels (0, 3, 6, 12, & 24 g N m−2) was used in this study. The responses of the plant in terms of growth (shoot length, leaf length and leaf width) were examined. Multiple regression equation was used for the model fit to determine the carbon content. The carbon content was found to be higher in all ambient and elevated CO2 conditions at the nitrogen addition level of 24 g N m−2.

The challenge of unsupervised person re-identification (ReID) lies in learning discriminative features without true labels. This paper formulates unsupervised person ReID as a multi-label classification task to progressively seek true labels. Our method starts by assigning each person image with a single-class label, then evolves to multi-label classification by leveraging the updated ReID model for label prediction. The label prediction comprises similarity computation and cycle consistency to ensure the quality of predicted labels. To boost the ReID model training efficiency in multi-label classification, we further propose the memory-based multi-label classification loss (MMCL). MMCL works with memory-based non-parametric classifier and integrates multi-label classification and single-label classification in a unified framework. Our label prediction and MMCL work iteratively and substantially boost the ReID performance. Experiments on several large-scale person ReID datasets demonstrate the superiority of our method in unsupervised person ReID. Our method also allows to use labeled person images in other domains. Under this transfer learning setting, our method also achieves state-of-the-art performance., Comment: CVPR2020