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Abstract. In this study, we developed a novel algorithm based on the collocatedModerate Resolution Imaging Spectroradiometer (MODIS) thermal infrared (TIR)observations and dust vertical profiles from the Cloud–Aerosol Lidar withOrthogonal Polarization (CALIOP) to simultaneously retrieve dust aerosoloptical depth at 10 µm (DAOD10 µm) and the coarse-mode dusteffective diameter (Deff) over global oceans. The accuracy of theDeff retrieval is assessed by comparing the dust lognormal volumeparticle size distribution (PSD) corresponding to retrieved Deff withthe in situ-measured dust PSDs from the AERosol Properties – Dust(AER-D), Saharan Mineral Dust Experiment (SAMUM-2), and Saharan Aerosol Long-Range Transport and Aerosol–Cloud-InteractionExperiment (SALTRACE) fieldcampaigns through case studies. The new DAOD10 µm retrievals wereevaluated first through comparisons with the collocated DAOD10.6 µmretrieved from the combined Imaging Infrared Radiometer (IIR) and CALIOPobservations from our previous study (Zheng et al., 2022). The pixel-to-pixelcomparison of the two DAOD retrievals indicates a good agreement(R∼0.7) and a significant reduction in (∼50 %) retrieval uncertainties largely thanks to the better constraint ondust size. In a climatological comparison, the seasonal and regional(2∘×5∘) mean DAOD10 µm retrievals basedon our combined MODIS and CALIOP method are in good agreement with the twoindependent Infrared Atmospheric Sounding Interferometer (IASI) productsover three dust transport regions (i.e., North Atlantic (NA; R=0.9),Indian Ocean (IO; R=0.8) and North Pacific (NP; R=0.7)). Using the new retrievals from 2013 to 2017, we performed a climatologicalanalysis of coarse-mode dust Deff over global oceans. We found thatdust Deff over IO and NP is up to 20 % smaller than that over NA.Over NA in summer, we found a ∼50 % reduction in the numberof retrievals with Deff>5 µm from 15 to35∘ W and a stable trend of Deff average at 4.4 µm from35∘ W throughout the Caribbean Sea (90∘ W). Over NP inspring, only ∼5 % of retrieved pixels with Deff>5 µm are found from 150 to 180∘ E, whilethe mean Deff remains stable at 4.0 µm throughout eastern NP. To the best of our knowledge, this study is the first to retrieve both DAOD andcoarse-mode dust particle size over global oceans for multiple years. Thisretrieval dataset provides insightful information for evaluating dustlongwave radiative effects and coarse-mode dust particle size in models.

Abstract. The role of mineral dust aerosol in the global radiative energy budget is oftenquantified by the dust direct radiative effect (DRE). The dust DRE stronglydepends on dust aerosol optical depth (DAOD), therefore, DRE efficiency(DREE = DRE / DAOD) is widely compared across different studies to eliminatedifferences due to the various dust loads. Nevertheless, DREE is stillinfluenced by the uncertainties associated with dust particle sizedistribution (PSD) and optical properties. In this study, we derive a globalclear-sky size-resolved DREE dataset in both shortwave (SW) and longwave (LW) at top ofthe atmosphere (TOA) and surface based on satellite observations (i.e.,satellite-retrieved dust extinction spatial and vertical distributions). Inthe DREE dataset, dust geometric diameter from 0.1 to 100 µmis divided into 10 bins and the corresponding monthly mean DREE (withrespect to DAOD at 532 nm) for each size bin is derived by using the RapidRadiative Transfer Model (RRTM). Three sets of state of the art dustrefractive indices (RI) and two sets of dust shape models (sphere vs. spheroid) are adopted to investigate the sensitivity of dust DREE to dustabsorption and shape. As a result, the size-resolved dust DREE datasetcontains globally distributed monthly mean dust DREE at TOA and surface foreach of 10 size bins with 5∘ (longitude) ×2∘(latitude) resolution as well as for each dust RI and shape combination. Thesize-resolved dust DREE dataset can be used to readily calculate global dustDRE for any DAOD and dust PSD, including the uncertainty in the DRE inducedby dust microphysical properties, (e.g., dust PSD, RI and shape). Bycalculating dust DRE based on DAOD climatology retrieved from differentsatellite sensors and based on different dust PSD, we find that uncertaintyin the spatial pattern of DAOD induces more than 10 % of the uncertaintyin SW dust DRE at TOA. The observation-based dust PSD induces around15–20 % uncertainty in dust DRE at TOA and in theatmosphere. The sensitivity assessments of dust DRE to dust RI and shapefurther suggest that dust nonsphericity induces a negligible effect on dustDRE estimations, while dust RI turns out to be the most important factor indetermining dust DRE, particularly in SW.

Existing regionalization methods tend to be either spatial attribute- or spatial interaction-based, while real-world tasks usually involve both considerations to satisfy multiple objectives simultaneously. In this research, we propose Multilayer Network Community Detection and Kernel Extension (MNCD-KE), a two-step regionalization framework, as a feasible solution for such tasks. First, spatial attributes are embedded into attributes of nodes in a spatial interaction-defined multilayer network, and the kernel and marginal parts of the regions are determined by giving the membership value of the regionalization units to network communities. Second, the final result is obtained through a kernel extension process considering geographical constraints, including spatial contiguity, size balance, morphological regularity, and existing boundary consistency of the regions. Empirical experiments show that the proposed method yields outcomes that, in maintaining comparable performances with most baseline algorithms with either 'attribute' or 'interaction' objectives as measured by the respective criteria, simultaneously meet the dual objectives with results intuitively comprehensible. Its low computing costs and parameter adjustment flexibility make the proposed framework a convenient approach for real-world multi-objective regionalization tasks. We conclude the research with discussions on the boundary conditions for the framework to work and their relevance to city science theories, along with practical implications. [ABSTRACT FROM AUTHOR]

The source of dust in the global atmosphere is an important factor to better understand the role of dust aerosols in the climate system. However, it is a difficult task to attribute the airborne dust over the remote land and ocean regions to their origins since dust from various sources are mixed during long‐range transport. Recently, a multi‐model experiment, namely the AeroCom‐III Dust Source Attribution (DUSA), has been conducted to estimate the relative contribution of dust in various locations from different sources with tagged simulations from seven participating global models. The BASE run and a series of runs with nine tagged regions were made to estimate the contribution of dust emitted in East‐ and West‐Africa, Middle East, Central‐ and East‐Asia, North America, the Southern Hemisphere, and the prominent dust hot spots of the Bodélé and Taklimakan Deserts. The models generally agree in large scale mean dust distributions, however models show large diversity in dust source attribution. The inter‐model differences are significant with the global model dust diversity in 30%–50%, but the differences in regional and seasonal scales are even larger. The multi‐model analysis estimates that North Africa contributes 60% of global atmospheric dust loading, followed by Middle East and Central Asia sources (24%). Southern hemispheric sources account for 10% of global dust loading, however it contributes more than 70% of dust over the Southern Hemisphere. The study provides quantitative estimates of the impact of dust emitted from different source regions on the globe and various receptor regions including remote land, ocean, and the polar regions synthesized from the seven models. Plain Language Summary: As the most abundant aerosol type in the Earth's atmosphere, mineral dust plays an important role in global climate by interacting with incoming and outgoing radiation, providing liquid and ice cloud nuclei, and affecting atmospheric stability. The global dust sources are relatively well characterized by the remote sensing and modeling studies as the majority of dust is emitted from the so‐called dust belt which expands from North Africa to East Asia. However, it is challenging to attribute dust sources over the remote land and ocean regions, since dust is mixed during long‐range transport, where it experiences complex atmospheric processes, including horizontal and vertical‐advection, wet deposition, and dry deposition. Using the multi‐model simulations in the Aerocom/Dust Source Attribution experiment, the present study (a) examines the model diversity in dust source attribution and (b) estimates the contribution of dust sources to various receptor regions, including remote land/ocean and the polar regions in different altitudes, from the multi‐model statistics. Beyond dust sources, many remote land, ocean, and polar regions are affected by a mixture of dust from various sources around the globe. Key Points: Contributions of various dust sources are quantitatively estimated in a multi‐model experimentContributions of various sources have different horizontal and vertical distributions and seasonalityDust near source regions are dominated by dust emitted in the upwind source regions; however many remote land, ocean, and polar regions are affected by a mixture of dust from various sources around the globe [ABSTRACT FROM AUTHOR]

1. Antibody–drug conjugates (ADCs) are an important class of cancer therapies. They are complex molecules, comprising an antibody, a cytotoxic payload, and a linker. ADCs intend to confer high specificity by targeting a unique antigen expressed predominately on the surface of the tumour cells than on the normal cells and by releasing the potent cytotoxic drug inside the tumour causing cytotoxic cell death. Despite high specificity to tumour antigens, many ADCs are associated with off-target and on-target off-tumour toxicities, often leading to safety concerns before achieving the desirable clinical efficacy. Therefore, it is crucial to improve the therapeutic index (TI) of ADCs to enable the full potential of this important therapeutic modality. 2. The review summarises current approaches to improve the translation of safety, pharmacokinetics, and TI of ADCs. Common safety findings of ADCs resulting from off-target and on-target toxicities and nonclinical approaches to de-risk ADC safety will be discussed; multiple approaches of using preclinical and clinical dose and exposure data to calculate TI to guide clinical dosing will be elaborated; different approaches to improve TI of ADCs, including selecting the right target, right payload-linker and patients, optimising physicochemical properties, and using fractionation dosing, will also be discussed. [ABSTRACT FROM AUTHOR]

The kinematics of the heald frame of a rotary dobby with two different modulator types are analyzed and compared. Kinematic mathematical models of the modulator main shaft, cam unit, and heald frame driven by the rotary dobby with a cam-slider modulator and a cam-link modulator were constructed based on two different cam contours derived from measured points on the conjugate cams of the two modulators. The motion characteristics of the two modulators and a null modulator, the cam unit, and the motion transmission unit are analyzed. The purpose of the present study was to establish the kinematic models, investigate the motion characteristics, and analyze their differences. At the same time, a calculation method for each motion transmission process was established and numerical models were developed. The results demonstrated that the two different modulators produce almost the same heald frame motion characteristics. Despite that both modulator types can be adapted to the requirements of a loom, the cam-link modulator can produce a more stable and reliable motion.