bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mandatory human rights due diligence laws in Europe: A mirage for rightsholders?
Authors: Deva Surya 
Published: February 2023

AbstractMandatory human rights due diligence (HRDD) laws in the European Union (EU) – both enacted and in the making – seem to be a promising tool to harden soft international standards in the business and human rights (BHR) field, the most prominent of these being the UN Guiding Principles on Business and Human Rights (UNGPs). This article develops a two-layered critique of mandatory HRDD laws. It problematizes the very concept of HRDD as articulated by the UNGPs. I will argue that due to various conceptual, operational and structural limitations, HRDD alone will not bring the desired changes for rightsholders, because this process does not address various asymmetries of power between corporations and affected communities. The second layer of critique concerns the content of mandatory HRDD laws enacted in France, the Netherlands, Switzerland, Norway and Germany. Assessing these laws vis-à-vis six preconditions required to protect effectively people and the planet from business-related harms, it is clear that these mandatory HRDD laws are half-hearted attempts to tame business-related human rights abuses and hold the relevant corporate actors accountable. In addition to developing more ambitious mandatory HRDD laws in future, states should employ a range of additional regulatory tools that pay greater attention to achieving outcomes, drawing red lines in certain situations, and promoting access to remedy and corporate accountability.
Conceptualizing the fiscal state: implications for sub-Saharan Africa
Authors: Jeppesen Matilde , Bak Ane Karoline , Kjær Anne Mette 
Published: February 2023

AbstractThis paper contributes to the debate on domestic revenue mobilization and state-building in the Global South by exploring the concept of fiscal states and the common assumption that such states are present in sub-Saharan Africa. We systematically review the diverse understandings of the fiscal state across relevant literatures to revisit its conceptualization. On that basis, we define the fiscal state as a state whose public revenue base is dominated by tax revenue and loans, and where the relationship between taxation and external and domestic borrowing is balanced and thereby sustainable and characterized by interdependence. We distinguish the fiscal state conceptually from the tax, debt, and rentier states and present a typology of these ideal state types, discussing illustrative empirical examples of different states in sub-Saharan Africa. These illustrate that not all sub-Saharan states can be categorized as fiscal states. This is important because when African states are regarded as fiscal states, assumptions are made about their economic structures; yet, to the extent that these are absent, fiscal policy reforms are unlikely to carry long-term positive effects.
Linking Ice‐Phase Microphysics to Raindrop Characteristics in Deep Convection: A Warm‐Sector Extreme Rainfall Case Study in Eastern China
Authors: Chen Gang , Zhao Kun , Wen Long , Yang Ji , Zheng Yuanyuan , Xu Fen , Lyu Fanchao , Sun Kangyuan , Sun Liangxiao 
Published: February 2023

AbstractIn this study, we examine the evolution of ice‐phase microphysics [polarimetric radar signatures and identified graupel and hail (GH) (hereafter, GH) distributions] and raindrop characteristics [drop size distribution (DSD) and rainfall intensity] in a warm‐sector extreme rainfall case during the Meiyu period in Eastern China. Deep convection is identified in this rainstorm, raindrop characteristics are found to be deeply affected by the GH distribution condition, heavy rainfall (rain rate >20 ) is basically contributed by convective samples with GH identified aloft. As GH height rises, number concentration and mean size of raindrops increase accordingly, leading to the growth of rainfall intensity. Extreme rainfall (rain rate >100 ) is majorly induced by deep convection with hail or widespread (over 10 km level) graupel, melting of the abundant highly‐rimed particles plays a dominant role in generating high concentration raindrops. By revealing the link between GH distribution conditions and raindrop characteristics, the study helps to understand the specific role of ice‐phase processes to the formation of low‐level raindrops in deep convection.
Understanding Models' Global Sea Surface Temperature Bias in Mean State: From CMIP5 to CMIP6
Authors: Zhang Qibei , Liu Bo , Li Shuanglin , Zhou Tianjun 
Published: February 2023

AbstractThis paper evaluates sea surface temperature (SST) biases of coupled models participating in Coupled Model Intercomparison Project Phase 5 (CMIP5) and CMIP6. Overall, CMIP6 models perform better than CMIP5 ones in reproducing SST climatology, with lower multi‐model ensemble mean (MME) globally averaged absolute bias (1.17 vs. 1.31 K). MME bias in global mean annual SST shifts from cooling (−0.09 ± 0.52 K) to warming (0.23 ± 0.60 K). Regionally, in CMIP6 cooling biases over the Northwest Pacific and North Atlantic are reduced by 20% and 18%, while warming biases over the Northeast Pacific, Southeast Atlantic and Southern Ocean are increased by 25%, 16% and 107% respectively. These changes are mainly attributed to the combined effects from aggravated positive (or alleviated negative) bias in clear‐sky surface downward longwave radiation, and alleviated negative bias in cloud radiative effect, partially reduced by enhanced cooling bias in clear‐sky surface downward shortwave radiation.
MMS Observations of Dayside Warm (Several eV to 100 eV) Ions in the Middle and Outer Magnetosphere
Authors: Goldstein J. , Burch J. L. , Fuselier S. A. , Gomez R. , Gonzalez C. A. , Kim M. J. , Mukherjee J. , Turner N. E. , Wilson M. E. 
Published: February 2023

AbstractWarm (several eV to 100 eV) ions are an important, and still poorly understood, component of the magnetospheric plasma environment. We present the first comprehensive statistical analysis of several distinct populations of warm ions in the dayside middle and outer magnetosphere. We analyze 7 months (1 September 2015–31 March 2016) of Magnetospheric Multiscale Hot Plasma Composition Analyzer data comprising 734,200 moments (density, temperature) and energy‐dependent pitch angle distributions (PADs) of three major ion species (H+, He+, and O+) with energy ≤100 eV. PADs are represented by an energy‐averaged index that characterizes the shape of the PAD as field‐aligned (FA), pancake, or isotropic. We use filtering by temperature, pitch angle, and concentration to distinguish different populations, and obtain new and more complete information about average density, temperature, PADs, and composition. Our analysis explores two known populations of warm ions: the warm plasmasphere (WPS) and the warm cloak/trough (C/T). The WPS is a higher‐temperature, higher‐L extension of the duskside plasmaspheric bulge, containing mostly trapped (pancake/isotropic) ions with an H+:He+:O+ order of ion dominance. The C/T contains mostly FA warm ions with a dawnward (duskward) temperature gradient for H+ (He+ and O+), lower densities, and an H+:O+:He+ order of ion dominance. The WPS‐C/T overlap contains a mixture of the two populations (e.g., FA He+ in WPS, trapped O+ in C/T). Pancake (FA) PADs are correlated with higher (lower) density/temperature. Our analysis also identifies warm ions in the low‐energy plasma sheet. Our work consolidates and systematically extends the characterizations of warm ions reported in previous studies.
MPAS‐A Variable‐Resolution Simulations for Summer Monsoon Over China: Comparison Between Global and Regional Configuration
Authors: Cheng Yiyuan , Hui Pinhong , Liu Dongqing , Fang Juan , Wang Shuyu , Wang Shuguang , Tang Jianping 
Published: February 2023

AbstractDriven by ERA‐Interim reanalysis, two climate simulations are conducted from April to August for 20 years (1998–2017) during the East Asia summer monsoon with Model for Prediction Across Scale‐Atmosphere (MPAS‐A). The global variable‐resolution (MPAS‐VR) and regional (MPAS‐RCM) configurations are adopted under the same model framework with 92–25 km mesh refinement centered over Mainland China (MPAS‐A experiments hereafter). MPAS‐VR allows flexible interactions across scales. Constrained by the “reanalysis‐based” lateral boundary conditions (LBCs), MPAS‐RCM could well capture the evolution of large‐scale fields and becomes a proper reference for evaluating MPAS‐VR. The evaluations are conducted for precipitation, near‐surface air temperature, and circulation features against observed climate. Two MPAS‐A experiments present comparable results for the mean climatology and interannual variability except that MPAS‐VR presents wet biases along the tropical ocean and underestimation in the Yangtze–Huaihe River basin. Compared with MPAS‐VR, MPAS‐RCM presents better daily variations and rain belts’ evolution, which demonstrates the crucial effects of the LBCs for the limited‐area model. The simulated circulation and moisture flux can explain most of the deviations. However, two MPAS‐A experiments show consistent results for the extreme precipitation frequency and the extreme indices over Mainland China. With the same dynamic core and model physics, those climate features are similarly resolved by the two simulations. Thus, the 92–25 km MPAS‐VR simulation is demonstrated as a promising tool for regional climate hindcast.
Dissolved Iron Concentration and the Solubility Inferred by Humic‐Like Fluorescent Dissolved Organic Matter in the Intermediate Water in the North Pacific Including the Marginal Seas
Authors: Yamashita Youhei , Nishioka Jun 
Published: February 2023

AbstractThe marginal seas have been found to be important external sources of dissolved iron (Fe) in the North Pacific through circulation of intermediate water. Here, we show comprehensive spatial distributions of dissolved Fe concentrations and Fe(III) solubilities inferred from humic‐like fluorescent dissolved organic matter (FDOMH) over the North Pacific, including the marginal seas, the Sea of Okhotsk, and the Bering Sea. FDOMH was used as a proxy of chemical speciation of dissolved Fe in the intermediate and deep waters where liner relationships were previously observed between FDOMH and Fe(III) solubility. When dissolved Fe concentration exceeds Fe(III) solubility, Fe(III) solubility is assumed to be equivalent to concentration of FDOMH‐Fe complexes, and excess dissolved Fe concentration above the Fe(III) solubility is assumed to be colloidal Fe which is not complexed with FDOMH. In the intermediate water, the dissolved Fe concentration exceeded the Fe(III) solubility in the marginal seas, while excess Fe(III) solubility was evident downstream of the intermediate water circulation, suggesting that the major dissolved Fe chemical form derived from shelf and slope sediments in the marginal seas changed from colloidal Fe to FDOMH‐Fe complexes. With the previous findings, namely the dominance of labile particulate Fe in total Fe in the intermediate water of the Sea of Okhotsk and the Bering Sea, we hypothesized that the average size of sediment‐derived Fe decreases during transportation by intermediate water, most likely due to reversible scavenging with the highest removal rate for labile particulate Fe and the lowest removal rate for FDOMH‐Fe complexes.
Human gene-engineered calreticulin mutant stem cells recapitulate MPN hallmarks and identify targetable vulnerabilities
Authors: Foßelteder Johannes , Pabst Gabriel , Sconocchia Tommaso , Schlacher Angelika , Auinger Lisa , Kashofer Karl , Beham-Schmid Christine , Trajanoski Slave , Waskow Claudia , Schöll Wolfgang , Sill Heinz , Zebisch Armin , Wölfler Albert , Thomas Daniel , Reinisch Andreas 
Published: February 2023

AbstractCalreticulin (CALR) mutations present the main oncogenic drivers in JAK2 wildtype (WT) myeloproliferative neoplasms (MPN), including essential thrombocythemia and myelofibrosis, where mutant (MUT) CALR is increasingly recognized as a suitable mutation-specific drug target. However, our current understanding of its mechanism-of-action is derived from mouse models or immortalized cell lines, where cross-species differences, ectopic over-expression and lack of disease penetrance are hampering translational research. Here, we describe the first human gene-engineered model of CALR MUT MPN using a CRISPR/Cas9 and adeno-associated viral vector-mediated knock-in strategy in primary human hematopoietic stem and progenitor cells (HSPCs) to establish a reproducible and trackable phenotype in vitro and in xenografted mice. Our humanized model recapitulates many disease hallmarks: thrombopoietin-independent megakaryopoiesis, myeloid-lineage skewing, splenomegaly, bone marrow fibrosis, and expansion of megakaryocyte-primed CD41+ progenitors. Strikingly, introduction of CALR mutations enforced early reprogramming of human HSPCs and the induction of an endoplasmic reticulum stress response. The observed compensatory upregulation of chaperones revealed novel mutation-specific vulnerabilities with preferential sensitivity of CALR mutant cells to inhibition of the BiP chaperone and the proteasome. Overall, our humanized model improves purely murine models and provides a readily usable basis for testing of novel therapeutic strategies in a human setting.
LncRNA MALAT1 promotes growth and metastasis of head and neck squamous cell carcinoma by repressing VHL through a non-canonical function of EZH2
Authors: Duan Yuansheng , Yue Kai , Ye Beibei , Chen Peng , Zhang Jin , He Qinghua , Wu Yue , Lai Qingchuan , Li Hong , Wu Yansheng , Jing Chao , Wang Xudong 
Published: February 2023

AbstractLong non-coding RNAs (LncRNAs) are implicated in malignant progression of human cancers. Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1), a well-known lncRNA, has been reported to play crucial roles in multiple malignancies including head and neck squamous cell carcinoma (HNSCC). However, the underlying mechanisms of MALAT1 in HNSCC progression remain to be further investigated. Here, we elucidated that compared with normal squamous epithelium, MALAT1 was notably upregulated in HNSCC tissues, especially in which was poorly differentiated or with lymph nodes metastasis. Moreover, elevated MALAT1 predicted unfavorable prognosis of HNSCC patients. The results of in vitro and in vivo assays showed that targeting MALAT1 could significantly weaken the capacities of proliferation and metastasis in HNSCC. Mechanistically, MALAT1 inhibited von Hippel–Lindau tumor suppressor (VHL) by activating EZH2/STAT3/Akt axis, then promoted the stabilization and activation of β-catenin and NF-κB which could play crucial roles in HNSCC growth and metastasis. In conclusion, our findings reveal a novel mechanism for malignant progression of HNSCC and suggest that MALAT1 might be a promising therapeutic target for HNSCC treatment.
SHQ1-associated neurodevelopmental disorder: Report of the first homozygous variant in unrelated patients and review of the literature
Authors: AlHargan Aljouhra , AlMuhaizea Mohammed A. , Almass Rawan , Alwadei Ali H. , Daghestani Maha , Arold Stefan T. , Kaya Namik 
Published: February 2023

AbstractCompound heterozygous mutations in SHQ1 have been associated with a rare and severe neurological disorder characterized by global developmental delay (GDD), cerebellar degeneration coupled with seizures, and early-onset dystonia. Currently, only five affected individuals have been documented in the literature. Here, we report three children from two unrelated families harboring a homozygous variant in the gene but with a milder phenotype than previously described. The patients had GDD and seizures. Magnetic resonance imaging analyses revealed diffuse white matter hypomyelination. Sanger sequencing confirmed the whole-exome sequencing results and revealed full segregation of the missense variant (SHQ1:c.833 T > C; p.I278T) in both families. We performed a comprehensive in silico analysis using different prediction classifiers and structural modeling of the variant. Our findings demonstrate that this novel homozygous variant in SHQ1 is likely to be pathogenic and leads to the clinical features observed in our patients.
A new paradigm of reliable sensing with field-deployed electrochemical sensors integrating data redundancy and source credibility
Authors: Saha Ajanta , Sedaghat Sotoudeh , Gopalakrishnan Sarath , Waimin Jose , Yermembetova Aiganym , Glassmaker Nicholas , Mousoulis Charilaos , Shakouri Ali , Wei Alexander , Rahimi Rahim , Alam Muhammad A. 
Published: February 2023

AbstractFor a continuous healthcare or environmental monitoring system, it is essential to reliably sense the analyte concentration reported by electrochemical sensors. However, environmental perturbation, sensor drift, and power-constraint make reliable sensing with wearable and implantable sensors difficult. While most studies focus on improving sensor stability and precision by increasing the system’s complexity and cost, we aim to address this challenge using low-cost sensors. To obtain the desired accuracy from low-cost sensors, we borrow two fundamental concepts from communication theory and computer science. First, inspired by reliable data transmission over a noisy communication channel by incorporating redundancy, we propose to measure the same quantity (i.e., analyte concentration) with multiple sensors. Second, we estimate the true signal by aggregating the output of the sensors based on their credibility, a technique originally developed for “truth discovery” in social sensing applications. We use the Maximum Likelihood Estimation to estimate the true signal and the credibility index of the sensors over time. Using the estimated signal, we develop an on-the-fly drift-correction method to make unreliable sensors reliable by correcting any systematic drifts during operation. Our approach can determine solution pH within 0.09 pH for more than three months by detecting and correcting the gradual drift of pH sensors as a function of gamma-ray irradiation. In the field study, we validate our method by measuring nitrate levels in an agricultural field onsite over 22 days within 0.06 mM of a high-precision laboratory-based sensor. We theoretically demonstrate and numerically validate that our approach can estimate the true signal even when the majority (~ 80%) of the sensors are unreliable. Moreover, by restricting wireless transmission to high-credible sensors, we achieve near-perfect information transfer at a fraction of the energy cost. The high-precision sensing with low-cost sensors at reduced transmission cost will pave the way for pervasive in-field sensing with electrochemical sensors. The approach is general and can improve the accuracy of any field-deployed sensors undergoing drift and degradation during operation.
One step surgical scene restoration for robot assisted minimally invasive surgery
Authors: Ali Shahnewaz , Jonmohamadi Yaqub , Fontanarosa Davide , Crawford Ross , Pandey Ajay K. 
Published: February 2023

AbstractMinimally invasive surgery (MIS) offers several advantages to patients including minimum blood loss and quick recovery time. However, lack of tactile or haptic feedback and poor visualization of the surgical site often result in some unintentional tissue damage. Visualization aspects further limits the collection of imaged frame contextual details, therefore the utility of computational methods such as tracking of tissue and tools, scene segmentation, and depth estimation are of paramount interest. Here, we discuss an online preprocessing framework that overcomes routinely encountered visualization challenges associated with the MIS. We resolve three pivotal surgical scene reconstruction tasks in a single step; namely, (i) denoise, (ii) deblur, and (iii) color correction. Our proposed method provides a latent clean and sharp image in the standard RGB color space from its noisy, blurred, and raw inputs in a single preprocessing step (end-to-end in one step). The proposed approach is compared against current state-of-the-art methods that perform each of the image restoration tasks separately. Results from knee arthroscopy show that our method outperforms existing solutions in tackling high-level vision tasks at a significantly reduced computation time.
Real-time nonlinear parameter estimation and tracking control of unmanned aerial vehicles in closed-loop
Authors: Imran Imil Hamda , Can Aydin , Stolkin Rustam , Montazeri Allahyar 
Published: February 2023

AbstractThe real-time unknown parameter estimation and adaptive tracking control problems are investigated in this paper for a six degrees of freedom (6-DOF) of under-actuated quadrotor unmanned aerial vehicle (UAV). A virtual proportional derivative (PD) controller is designed to maintain the translational dynamics. Two adaptive schemes are developed to handle the attitude dynamics of the UAV with several unknown parameters. In the beginning, a classical adaptive scheme (CAS) using the certainty equivalence principle is proposed and designed. The idea is to design a controller for an ideal situation by assuming the unknown parameters were known. Then the unknown parameters are replaced by their estimation. A theoretical analysis is provided to ensure the trajectory tracking of the adaptive controller. However, an inherent drawback of this scheme is that there is no guarantee for the estimated parameters to converge to the actual values. To address this issue, a new adaptive scheme (NAS) is developed as the next step by adding a continuously differentiable function to the control structure. The proposed technique guarantees handling of the parametric uncertainties with an appropriate design manifold. A rigorous analytical proof, numerical simulation analyses, and experimental validation are presented to show the effectiveness of the proposed control design.
Carbon nanotubes and nanobelts as potential materials for biosensor
Authors: Monavari Seyyed Mostafa , Marsusi Farah , Memarian Nafiseh , Qasemnazhand Mohammad 
Published: February 2023

AbstractWe investigate the electronic response of single-walled carbon nanotubes (SWCNTs) and a carbon nanobelt (CNB) to N-linked and O-linked SARS-CoV-2 spike glycoproteins, using ab initio quantum mechanical approach. The CNTs are selected from three zigzag, armchair, and chiral groups. We examine the effect of carbon nanotube (CNT) chirality on the interaction between CNTs and glycoproteins. Results indicate that the chiral semiconductor CNTs clearly response to the presence of the glycoproteins by changing the electronic band gaps and electron density of states (DOS). Since the changes in the CNTs band gaps in the presence of N-linked are about two times larger than the changes in the presence of the O-linked glycoprotein, chiral CNT may distinguish different types of the glycoproteins. The same results are obtained from CNBs. Thereby, we predict CNBs and chiral CNTs have suitable potential in sequential analysis of N- and O-linked glycosylation of the spike protein.
Assessing the impact of one million COVID-19 deaths in America: economic and life expectancy losses
Authors: Silva Sachin , Goosby Eric , Reid Michael J. A. 
Published: February 2023

AbstractBetween February 2020 and May 2022, one million Americans have died of COVID-19. To determine the contribution of those deaths to all-cause mortality in terms of life expectancy reductions and the resulting economic welfare losses, we calculated their combined impact on national income growth and the added value of lives lost. We estimated that US life expectancy at birth dropped by 3.08 years due to the million COVID-19 deaths. Economic welfare losses estimated in terms of national income growth supplemented by the value of lives lost, was in the order of US$3.57 trillion. US$2.20 trillion of these losses were in in the non-Hispanic White population (56.50%), US$698.24 billion (19.54%) in the Hispanic population, and US$579.93 billion (16.23%) in the non-Hispanic Black population. The scale of life expectancy and welfare losses underscores the pressing need to invest in health in the US to prevent further economic shocks from future pandemic threats.