bluuebunny/crossref_metadata_2025_split huggingface dataset:
Effect of Remote Ischaemic Conditioning on the Inflammatory Cytokine Cascade of COVID-19 (RIC in COVID-19): a Randomized Controlled Trial
Authors: Lukhna Kishal , do Carmo Helison R. P. , Castillo Alejandro Rossell , Davidson Sean M. , Geffen Hayli , Giesz Sara , Golforoush Pelin , Bovi Ticiane Gonçalez , Gorag Diana , Salama Alan , Imamdin Aqeela , Kalkhoran Siavash , Lecour Sandrine , Perroud Mauricio W. , Ntsekhe Mpiko , Sposito Andrei C. , Yellon Derek M. 
Published: November 2022

Abstract

Purpose

Patients hospitalized with COVID-19 may develop a hyperinflammatory, dysregulated cytokine “storm” that rapidly progresses to acute respiratory distress syndrome, multiple organ dysfunction, and even death. Remote ischaemic conditioning (RIC) has elicited anti-inflammatory and cytoprotective benefits by reducing cytokines following sepsis in animal studies. Therefore, we investigated whether RIC would mitigate the inflammatory cytokine cascade induced by COVID-19.

Methods
We conducted a prospective, multicentre, randomized, sham-controlled, single-blind trial in Brazil and South Africa. Non-critically ill adult patients with COVID-19 pneumonia were randomly allocated (1:1) to receive either RIC (intermittent ischaemia/reperfusion applied through four 5-min cycles of inflation (20 mmHg above systolic blood pressure) and deflation of an automated blood-pressure cuff) or sham for approximately 15 days. Serum was collected following RIC/sham administration and analyzed for inflammatory cytokines using flow cytometry. The endpoint was the change in serum cytokine concentrations. Participants were followed for 30 days.

Results
Eighty randomized participants (40 RIC and 40 sham) completed the trial. Baseline characteristics according to trial intervention were overall balanced. Despite downward trajectories of all cytokines across hospitalization, we observed no substantial changes in cytokine concentrations after successive days of RIC. Time to clinical improvement was similar in both groups (HR 1.66; 95% CI, 0.938–2.948, p 0.08). Overall RIC did not demonstrate a significant impact on the composite outcome of all-cause death or clinical deterioration (HR 1.19; 95% CI, 0.616–2.295, p = 0.61).

Conclusion
RIC did not reduce the hypercytokinaemia induced by COVID-19 or prevent clinical deterioration to critical care.

Trial Registration
ClinicalTrials.gov Identifier: NCT04699227.
Are mGluR2/3 Inhibitors Potential Compounds for Novel Antidepressants?
Authors: Jiang Yajie , Zou Manshu , Ren Tingting , Wang Yuhong 
Published: November 2022

AbstractDepression is the most common mental illness characterized by anhedonia, avolition and loss of appetite and motivation. The majority of conventional antidepressants are monoaminergic system selective inhibitors, yet the efficacies are not sufficient. Up to 30% of depressed patients are resistant to treatment with available antidepressants, underscoring the urgent need for development of novel therapeutics to meet clinical needs. Recent years, compounds acting on the glutamate system have attracted wide attention because of their strong, rapid and sustained antidepressant effects. Among them, selective inhibitors of metabotropic glutamate receptors 2 and 3 (mGluR2/3) have shown robust antidepressant benefits with fewer side-effects in both preclinical and clinical studies. Thus, we here attempt to summarize the antidepressant effects and underlying mechanisms of these inhibitors revealed in recent years as well as analyze the potential value of mGluR2/3 selective inhibitors in the treatment of depression.
The organization of the human organ trade: a comparative crime script analysis
Authors: Ambagtsheer Frederike , Bugter Roos 
Published: November 2022

AbstractThis study fills critical knowledge gaps into the organization of organ trade utilizing crime script analysis. Adopting a situational crime prevention approach, this article draws from law enforcement data to compare the crime commission process (activities, cast and locations) of 2 prosecuted organ trade cases: the Medicus case and the Netcare case. Both cases involved transnational criminal networks that performed kidney transplants from living donors. We further present similarities and differences between illegal and legal living donor kidney transplants that may help guide identification and disruption of illegal transplants. Our analysis reveal the similar crime trajectories of both criminal cases, in particular the extensive preparations and high degree of organization that were needed to execute the illegal transplants. Offenders in the illegal transplant schemes utilized the same opportunity structures that facilitate legal transplants, such as transplant units, hospitals and blood banks. Our results indicate that the trade is embedded within the transplant industry and intersects with the transport- and hospitality sector. The transplant industry in the studied cases was particularly found to provide the medical infrastructure needed to facilitate and sustain organ trade. When compared to legal transplants, the studied illegal transplant scripts reveal a wider diversity in recruitment tactics and concealment strategies and a higher diversity in locations for the pre-operative work-up of donors and recipients. The results suggest the need for a broader conceptualization of the organ trade that incorporates both organized crime and white collar crime perspectives.
Role of female teachers of childhood education in directing children towards effective use of smart devices
Authors: Al-Barakat Ali Ahmad , Al-Hassan Omayya M. , AlAli Rommel Mahmoud , Al-Hassan Mu’aweya Mohammad , Al sharief Ramzia Ali 
Published: November 2022

AbstractThis study endeavors to investigate the role of female teachers of childhood education in directing children towards the effective use of smart devices in developing their learning experiences. The sample of the study consisted of 83 female teachers in the northern region of Jordan, who were selected using the available sampling method. To achieve the aim of the study, a semi-structured interview was prepared and its validity and consistency were verified.The results shown that childhood education female teachers achieved advanced roles in directing children towards the effective use of smart devices, where effective direction towards the use of smart devices was represented in: directing children to self-organize their learning during using smart devices, directing children to acquire digital social interaction skills and directing them to learn innovation during using smart devices, with the importance of directing them to avoid the harms of using smart devices through preventive guidance.Moreover, the findings of the study revealed the importance of directing children to participate in various digital activities, as well as directing them to learn through digital applications that are purposeful and suitable to their mental capabilities. Based on the research findings, the study presented a number of relevant recommendations.
A typology for digital leadership in higher education: the case of a large-scale mobile technology initiative (using tablets)
Authors: Ghamrawi Norma , M. Tamim Rana 
Published: November 2022

AbstractThis study investigated a digital reform initiative, rated excellent by the government, of one higher education institution (HEI) in an Arab State in the Gulf. The focus of the study was to develop a digital typology, while exploring the leadership attributes that characterized the core leadership team, as they accomplished the migration towards a digital culture in one year, within a context where faculty members showed resistance against digitalization. The study was conducted immediately after the implementation of the initiative that took place over the course of one year, just before the Covid-19 pandemic. Semi-structured interviews were conducted with all the six key individuals in the leadership team who led this initiative. Data was analyzed using content-based analysis. Findings of the study were used to synthesize a 5D typology for digital leadership attributes: (1) Digital competence; (2) Digital culture; (3) Digital Differentiation; (4) Digital governance; and (5) Digital advocacy. The paper provides in depth discussion how these attributes supported the adaptive ability of a Higher Education Institution towards accepting digitalization.
Jellyfish blooms challenge the provisioning of ecosystem services in the Korean coastal waters
Authors: Lee Sun-Hee , Scotti Marco , Jung Sukgeun , Hwang Jiang-Shiou , Molinero Juan Carlos 
Published: November 2022

AbstractTemperate fisheries grounds are exposed to compound effects of jellyfish proliferations and fishing pressure, which affect local fisheries, cause economic losses, and threaten seafood supply. Here, we quantify the interlink between climate variability and jellyfish blooms and their impact on the Japanese anchovy (Engraulis japonicus), in the Korean coastal waters. We used a bioclimate dataset (2010–2019) that includes quantitative information of two major bloom-former species, Aurelia coerulea and Nemopilema nomurai, in the Korean Peninsula. We show that climate phenomena governing East Asia regions explain circa half of jellyfish variability. In turn, jellyfish blooms have a significant negative effect on anchovy interannual changes (r = -0.47, P < 0.01), which varies along with the bloom magnitude. Our results indicate that the intensity of jellyfish blooms, more than their duration, has a predominant effect on anchovy and coastal fisheries production. We also suggest the possibility of using climate signals for assessing and eventually predicting, interannual abundance changes of jellyfish in the Korean Peninsula. These results stress the challenge posed by jellyfish blooms to the provisioning of ecosystem services via their influence on marine harvested fish and further highlight the need for their integration into ecosystem-based management.
Organic litter dynamics in headwater streams draining contrasting land uses
Authors: Pye Marian C. , Vaughan Ian P. , Ormerod Steve J. , Durance Isabelle 
Published: November 2022

AbstractClimate change could alter fluxes of organic matter and macronutrients through freshwater ecosystems potentially affecting stream organisms. However, riparian controls on litter dynamics offer an opportunity to adapt headwaters to climate change by protecting or restoring riparian vegetation. We assessed how riparian land cover and climatic variability affected the supply, retention and downstream transport of particulate organic matter (POM) in headwaters—the most extensive small water bodies in temperate landscapes. Leaf litter inputs, benthic stocks and suspended organic matter were measured nominally monthly in second–third-order streams draining broadleaf woodland, conifer, acid moorland and circumneutral moorland over four years with varying discharge. Streams draining broadleaf woodland received more leaf litter from the riparian zone than conifer and moorland and transported higher concentrations of CPOM and FPOM at base flows. Broadleaf sites had higher CPOM stocks, even after hydrological events that reduced CPOM in conifer and moorland sites. In contrast, FPOM dynamics reflected hydrological conditions irrespective of land cover. These results show how some organic matter fractions in streams are sensitive to hydrological conditions, illustrating how wetter climates will influence FPOM exports. Nevertheless, riparian broadleaves have the potential to offset climatic effects on organic matter processing in headwaters through the replenishment and retention of CPOM.
On Nontrivial Weak Dicomplementations and the Lattice Congruences that Preserve Them
Authors: Kwuida Leonard , Mureşan Claudia 
Published: November 2022

AbstractWe study the existence of nontrivial and of representable (dual) weak complementations, along with the lattice congruences that preserve them, in different constructions of bounded lattices, then use this study to determine the finite (dual) weakly complemented lattices with the largest numbers of congruences, along with the structures of their congruence lattices. It turns out that, if $$n\ge 7$$

n
≥
7

is a natural number, then the four largest numbers of congruences of the n–element (dual) weakly complemented lattices are: $$2^{n-2}+1$$

2

n
-
2

+
1

, $$2^{n-3}+1$$

2

n
-
3

+
1

, $$5\cdot 2^{n-6}+1$$

5
·

2

n
-
6

+
1

and $$2^{n-4}+1$$

2

n
-
4

+
1

, which yields the fact that, for any $$n\ge 5$$

n
≥
5

, the largest and second largest numbers of congruences of the n–element weakly dicomplemented lattices are $$2^{n-3}+1$$

2

n
-
3

+
1

and $$2^{n-4}+1$$

2

n
-
4

+
1

. For smaller numbers of elements, several intermediate numbers of congruences appear between the elements of these sequences.
Plant strategies to mine iron from alkaline substrates
Authors: Vélez-Bermúdez Isabel Cristina , Schmidt Wolfgang 
Published: November 2022

AbstractIn concert with oxygen, soil alkalinity strongly restricts the availability of iron, an essential nutrient with a multitude of functions in living organisms. In addition to its role in mitochondrial energy metabolism and as a cofactor for enzymes, in plants iron also plays key roles in photosynthesis and is required for chlorophyll biosynthesis. The ability to thrive in calcareous soils, referred to as calcicole behaviour, is the readout of an amalgam of traits of which efficient foraging of iron is a decisive factor. Recently, the well-established concept of two distinct iron uptake strategies, phylogenetically separating grasses from other land plants, was expanded by the discovery of auxiliary mechanisms that extend the range of edaphic conditions to which a species can adapt. Secretion of a tailor-made cocktail of iron-mobilising metabolites into the rhizosphere, the composition of which is responsive to a suite of edaphic and internal cues, allows survival in calcareous soils through a competitive iron acquisition strategy, which includes intricate interactions with the consortium of associated microorganisms in, on, and around the roots. This versatile, reciprocal plant-microbiome interplay affects iron mobilisation directly, but also collaterally by impacting growth, fitness, and health of the host. Here, we review the mechanisms and the multifaceted regulation of iron acquisition in plants, taking into consideration the specific constraints associated with the uptake of iron from alkaline soils. Knowledge on how plants extract iron from such soils sets the stage for a better understanding of essential ecological processes and for combatting iron malnutrition in humans.
Maternal Employment Shapes Daughters’ Employment Stability in Egypt: Evidence for the Intergenerational Transmission of Labor Force Attachment
Authors: Abouelenin Mariam , Hu Yang 
Published: November 2022

AbstractResearch has documented how maternal employment influences daughters’ participation in paid employment. However, we know far less about how maternal employment during daughters’ adolescence relates to the daughters’ subsequent employment stability. Analyzing data from three waves (2006, 2012, and 2018) of the Egypt Labor Market Panel Survey (N = 3,345) using structural equation models, this study compares the employment stability of women with and without working mothers during adolescence and examines how the influence of maternal employment on daughters’ employment stability varies with employment sector. Furthermore, a decomposition method is applied to determine the extent to which daughters’ education mediates the association between maternal employment and their employment stability. The results show that mothers’ employment is positively associated with their adult daughters’ employment stability. This intergenerational association is sector specific: mothers’ employment in a given sector only bolsters their daughters’ employment stability in the same sector. The daughter’s education mediates only a small portion of the intergenerational association in the public sector. The findings highlight the important role of Egypt’s institutional settings in configuring the intergenerational transmission of employment stability among women, and suggest that policies that support working mothers have the potential to bolster their daughters’ long-term labor market attachment.
A hybrid CUDA, OpenMP, and MPI parallel TCA-based domain adaptation for classification of very high-resolution remote sensing images
Authors: Garea Alberto S. , Heras Dora B. , Argüello Francisco , Demir Begüm 
Published: November 2022

AbstractDomain Adaptation (DA) is a technique that aims at extracting information from a labeled remote sensing image to allow classifying a different image obtained by the same sensor but at a different geographical location. This is a very complex problem from the computational point of view, specially due to the very high-resolution of multispectral images. TCANet is a deep learning neural network for DA classification problems that has been proven as very accurate for solving them. TCANet consists of several stages based on the application of convolutional filters obtained through Transfer Component Analysis (TCA) computed over the input images. It does not require backpropagation training, in contrast to the usual CNN-based networks, as the convolutional filters are directly computed based on the TCA transform applied over the training samples. In this paper, a hybrid parallel TCA-based domain adaptation technique for solving the classification of very high-resolution multispectral images is presented. It is designed for efficient execution on a multi-node computer by using Message Passing Interface (MPI), exploiting the available Graphical Processing Units (GPUs), and making efficient use of each multicore node by using Open Multi-Processing (OpenMP). As a result, an accurate DA technique from the point of view of classification and with high speedup values over the sequential version is obtained, increasing the applicability of the technique to real problems.
An Investigation of the Impact and Resilience of British High Streets Following the COVID-19 Lockdown Restrictions
Authors: Hill Abigail , Cheshire James 
Published: November 2022

AbstractBritish high streets have faced significant economic and cultural challenges as a consequence of the COVID-19 pandemic. This is predominantly due to government enforced restrictions which required all ‘non-essential’ retail to close, resulting in a significant change in the way consumers interacted with high streets. While all premises related to the retail or hospitality sector were forced to close, leading to rising vacancy rates, some high streets were more resilient to the economic shock than others. In this paper we detect some of the unforeseen consequences of the pandemic on British high streets and create a measure of resilience. The impact of the lockdown restrictions have resulted in some high streets, notably Spring Street in Paddington, London, experiencing disproportionate decline. Others including Northolt Road in Harrow, London were able maintain their occupancy. This study provides a typology of high street resilience incorporating the impact of the COVID-19 lockdown restrictions and links the impact of government policy to the economic performance of high streets. The outcomes from this research address both local and national policy contexts as the resilience typology has the potential to assist in funding allocation for recovery and regeneration projects.
Machine learning predicting and engineering the yield, N content, and specific surface area of biochar derived from pyrolysis of biomass
Authors: Leng Lijian , Yang Lihong , Lei Xinni , Zhang Weijin , Ai Zejian , Yang Zequn , Zhan Hao , Yang Jianping , Yuan Xingzhong , Peng Haoyi , Li Hailong 
Published: November 2022

AbstractBiochar produced from pyrolysis of biomass has been developed as a platform carbonaceous material that can be used in various applications. The specific surface area (SSA) and functionalities such as N-containing functional groups of biochar are the most significant properties determining the application performance of biochar as a carbon material in various areas, such as removal of pollutants, adsorption of CO2and H2, catalysis, and energy storage. Producing biochar with preferable SSA and N functional groups is among the frontiers to engineer biochar materials. This study attempted to build machine learning models to predict and optimize specific surface area of biochar (SSA-char), N content of biochar (N-char), and yield of biochar (Yield-char) individually or simultaneously, by using elemental, proximate, and biochemical compositions of biomass and pyrolysis conditions as input variables. The predictions of Yield-char, N-char, and SSA-char were compared by using random forest (RF) and gradient boosting regression (GBR) models. GBR outperformed RF for most predictions. When input parameters included elemental and proximate compositions as well as pyrolysis conditions, the test R2values for the single-target and multi-target GBR models were 0.90–0.95 except for the two-target prediction of Yield-char and SSA-char which had a test R2of 0.84 and the three-target prediction model which had a test R2of 0.81. As indicated by the Pearson correlation coefficient between variables and the feature importance of these GBR models, the top influencing factors toward predicting three targets were specified as follows: pyrolysis temperature, residence time, and fixed carbon for Yield-char; N and ash for N-char; ash and pyrolysis temperature for SSA-char. The effects of these parameters on three targets were different, but the trade-offs of these three were balanced during multi-target ML prediction and optimization. The optimum solutions were then experimentally verified, which opens a new way for designing smart biochar with target properties and oriented application potential.Graphical Abstract
Understanding internal migration in the UK before and during the COVID-19 pandemic using twitter data
Authors: Wang Yikang , Zhong Chen , Gao Qili , Cabrera-Arnau Carmen 
Published: November 2022

AbstractThe COVID-19 pandemic has greatly affected internal migration patterns and may last beyond the pandemic. It raises the need to monitor the migration in an economical, effective and timely way. Benefitting from the advancement of geolocation data collection techniques, we used near real-time and fine-grained Twitter data to monitor migration patterns during the COVID-19 pandemic, dated from January 2019 to December 2021. Based on geocoding and estimating home locations, we proposed five indices depicting migration patterns, which are demonstrated by applying an empirical study at national and local authority scales to the UK. Our findings point to complex social processes unfolding differently over space and time. In particular, the pandemic and lockdown policies significantly reduced the rate of migration. Furthermore, we found a trend of people moving out of large cities to the nearby rural areas, and also conjunctive cities if there is one, before and during the peak of the pandemic. The trend of moving to rural areas became more significant in 2020 and most people who moved out had not returned by the end of 2021, although large cities recovered more quickly than other regions. Our results of monthly migration matrixes are validated to be consistent with official migration flow data released by the Office for National Statistics, but have finer temporal granularity and can be updated more frequently. This study demonstrates that Twitter data is highly valuable for migration trend analysis despite the biases in population representation.