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Urbanization has resulted in deterioration of natural lands and extinction of indigenous species. Domestic gardens are neglected spots of plants biodiversity. This research aimed to assess domestic garden plants diversity, composition, distribution, and identify the conserved indigenous plant species in a heavily urbanized arid city. Domestic gardens within each district were randomly selected, visited, and surveyed. Cultivated plant species in gardens were identified and counted; their frequencies and abundance levels were calculated. Plant species richness, Shannon, evenness, and Simpson's indices were calculated. More than 12,000 plants belonging to 223 plant species compromising 72 plant families were found. Domestic gardens played a significant role in conserving regionally extinct or endangered native plant species while undesirably sustained exotic and invasive plants. Overall, exotic plants species represented 84% of all identified species. The highest percentage of native plants (29%) was found in Uhod district, while the lowest (11%) was in Jubaiha district. The minimum and maximum proportion of medicinal, poisonous, and fruit bearing plants on a district bases were 9–26%, 9–22%, and 11–43% of domestic garden plants, respectively. The highest species richness (103) was in Zahran, while the lowest (20) was in Al-Madinah district. Shannon diversity index was the highest in Zahran and Sweileh districts. Shannon, evenness, and Simpson diversity indexes revealed Badr Al-Jadidah as the lowest plant diversity district. District history, lots sizes, garden sizes, socioeconomic status, residents' preferences, and housing regulations resulted in variation in plants diversity and species composition. Thus, monitoring species composition in domestic gardens and raising public awareness about plants benefits/risks supports environmental sustainability. Attention should be given to these neglected biodiversity hotspots, especially in arid environments. [ABSTRACT FROM AUTHOR]

Chemical reaction networks are powerful tools for modeling cell signaling and its disruptions in diseases like cancer. Realistic chemical reaction networks involve hundreds of proteins and reactions, resulting in a model depending on a consistently large number of kinetic parameters. Since finely calibrating all the parameters would require an unrealistic amount of data, proper sensitivity analysis is required to identify a subset of parameters for which fine tuning is needed and thus provide a fundamental tool for the qualitative analysis of the network. We present a multidisciplinary approach for computing a set of synthetic sensitivity indices. These indices rank the kinetic parameters, based on the impact that errors in their values would have on the protein concentration profile at equilibrium. Our tests on a chemical reaction network devised for colorectal cells demonstrate the effectiveness of the considered sensitivity indices in different scenarios including in-silico drug dosage and novel therapeutic target discovery. The Matlab code for computing the synthetic sensitivity indices and the data concerning the network for colorectal cells are available at https://github.com/theMIDAgroup/CRN_sensitivity. [ABSTRACT FROM AUTHOR]

This paper presents a novel adaptive iterative learning control (AILC) scheme to improve the tracking performance of the manipulator for spraying hull to achieve high-quality spraying effectively. First, a novel way of modifying the reference trajectory is proposed to deal with arbitrary initial states and iteration-varying reference trajectory when the manipulator reciprocates spraying. The modified way comprises constructing an error variable containing an initial correction term and determining the shortest limited time of completely tracking the desired trajectory by optimization principle. Based on this, an AILC scheme uses adaptive and backstepping techniques to handle the system's uncertain physical parameters and external disturbance. Theoretically, this control scheme can guarantee the tip-position of the spraying manipulator to perfectly track the desired reference trajectory within an appropriate, limited time under arbitrary initial states and iteration-varying reference trajectory. Simulations and experiments verify the proposed method's effectiveness and advantage by comparison with other control algorithms. [ABSTRACT FROM AUTHOR]

The aim of this policy paper is to characterize the current situation of Tunisian municipalities in matters of climate change policies and actions and to understand the barriers and best practices. By surveying municipalities in Tunisia, we were able to provide an overview of the Tunisian municipalities in matters of climate change actions and strategies, as well as finding the main barriers and best practices. First, we found that most Tunisian municipalities are facing different effects of climate change. Second, the majority of municipalities do not have a strategy for mitigation and adaptation of climate change at the local level. Third, the main barrier that municipalities face in investing in climate change actions is the lack of financial resources and funding. Four, we have identified some of the best climate change mitigation and adaptation practices of surveyed cities, which should be taken into consideration and implemented also by the other cities. [ABSTRACT FROM AUTHOR]