bluuebunny/crossref_metadata_2025_split huggingface dataset:
Gesture recognition method based on misalignment mean absolute deviation and KL divergence
Authors: Tian Yong , Zhuang Chuanzhen , Cui Jiadong , Qiao Runjie , Ding Xuejun 
Published: September 2022

AbstractAt present, it has become very convenient to collect channel state information (CSI) from ubiquitous commercial WiFi network cards, and the location or activity of a human who affects the CSI can be recognized by analyzing the change of the CSI. Therefore, wireless sensing technology based on the CSI has received widespread attention. However, the existing CSI-based gesture recognition methods still have some problems, which include that subcarrier selection is not optimized and motion interval extraction is not accurate enough, so the accuracy of gesture recognition methods still needs to be further improved. In response to the above problems, a gesture recognition method based on misalignment mean absolute deviation (MMAD) and KL divergence is proposed in the paper, which is called MMAD-KL-GR method. This method uses the proposed MMAD algorithm to extract the CSI amplitude intervals containing gesture information, then selects subcarriers by comparing the KL divergence of the CSI amplitude, and finally uses the subspace K-nearest neighbor (KNN) algorithm to recognize the gestures. Several experiments show that the MMAD-KL-GR method can effectively improve the accuracy of the gesture recognition.
MF-GCN-LSTM: a cloud-edge distributed framework for key positions prediction in grid projects
Authors: Huang Shaoyuan , Zhang Yuxi , Peng Guozheng , Zhao Juan , Zhu Keping , Zhang Heng , Wang Xiaofei 
Published: September 2022

AbstractIn this article, we solve the key positions prediction problem of engineering projects in smart grid, which pays more attention to the spatial-temporal distribution of projects. Many studies show that the projects are affected by multi-dimensional features such as time, space, correlation etc. However, few work can accurately predict the key positions of projects based on multi-dimensional features. In order to solve this problem, we propose the idea of multi-feature extraction, and make use of the real-world records trace to conduct multi-dimensional modeling. Then we introduce a multi-dimensional features extraction model: Multi-Feature-based GCN-LSTM (MF-GCN-LSTM) to take the effect of time, space and correlation for predicting the key positions of projects. Experiments on different datasets with various project types have proved that our model can complete the key positions prediction task efficiently. Compared with the other traditional method and non-linear models, our model shows higher prediction accuracy and robustness. Moreover, we show that the whole prediction framework MF-GCN-LSTM can be split and deployed in a distributed manner to accelerate the inference of the model under the cloud edge system.
CD7-directed CAR T-cell therapy: a potential immunotherapy strategy for relapsed/refractory acute myeloid leukemia
Authors: Cao Xuanqi , Dai Haiping , Cui Qingya , Li Zheng , Shen Wenhong , Pan Jinlan , Shen Hongjie , Ma Qinfen , Li Mengyun , Chen Sifan , Chen Juncheng , Zhu Xiaming , Meng Huimin , Yang Lin , Wu Depei , Tang Xiaowen 
Published: September 2022

AbstractRelapsed/refractory acute myeloid leukemia (AML) patients generally have a dismal prognosis and the treatment remains challenging. Due to the expression of CD7 on 30% AML and not on normal myeloid and erythroid cells, CD7 is an attractive target for immunotherapy of AML. CD7-targeted CAR T-cells had demonstrated encouraging efficacy in xenograft models of AML. We report here on the use of autologous CD7 CAR T-cells in the treatment of a relapsed/refractory AML patient with complex karyotype, TP53 deletion, FLT3-ITD mutation, and SKAP2-RUNX1 fusion gene. Before the CAR T-cell therapy, the patient achieved partial remission with IA regimen and attained complete remission after reinduction therapy (decitabine and venentoclax). Relapse occurred after consolidation (CLAG regimen). Then she failed CLIA regimen combined with venetoclax and exhibited resistance to FLT3 inhibitors. Bone marrow showed 20% blasts (CD7+ 95.6%). A total dose of 5 × 106/kg CD7 CAR T-cells was administered after the decitabine +FC regimen. Seventeen days after CAR T-cells infusion, she achieved morphologic leukemia-free state. The patient developed grade 3 cytokine release syndrome. No severe organ toxicity or immune effector cell-associated neurotoxicity syndrome was observed. In summary, the autologous CD7 CAR T-cell therapy could be considered a potential approach for AML with CD7 expression (NCT04762485).Trial registration Clinical Trials.gov, NCT04762485. Registered on February 21, 2021, prospectively registered
Assessment of deep geothermal research and development in the Upper Rhine Graben
Authors: Frey Matthis , Bär Kristian , Stober Ingrid , Reinecker John , van der Vaart Jeroen , Sass Ingo 
Published: September 2022

AbstractDeep geothermal energy represents a key element of future renewable energy production due to its base load capability and the almost inexhaustible resource base. Especially with regard to heat supply, this technology offers a huge potential for carbon saving. One of the main targets of geothermal projects in Central Europe is the Upper Rhine Graben, which exhibits elevated subsurface temperatures and reservoirs with favorable hydraulic properties. Several decades of intensive research in the region resulted in a comprehensive understanding of the geological situation. This review study summarizes the findings relevant to deep geothermal projects and thus provides a useful working and decision-making basis for stakeholders. A total of nine geological units have been identified that are suitable for deep geothermal exploitation, comprising the crystalline basement, various sandstone formations and Mesozoic carbonates. An extensive lithostratigraphic, structural, geochemical, hydraulic and petrophysical characterization is given for each of these potential reservoirs. This paper furthermore provides an overview of the available data and geological as well as temperature models.
Influence of management practice on the microbiota of a critically endangered species: a longitudinal study of kākāpō chick faeces and associated nest litter
Authors: West Annie G. , Digby Andrew , Lear Gavin ,   Kākāpō Recovery Team,   Kākāpō Aspergillosis Research Consortium, Digby Andrew , Armstrong Doug , Armstrong-James Darius , Bromley Mike , Buckley Elizabeth , Chatterton James , Cox Murray P. , Cramer Robert A. , Crane Jodie , Dearden Peter K. , Eason Daryl , Fisher Matthew C. , Gago Sara , Gartrell Brett , Gemmell Neil J. , Glare Travis R. , Guhlin Joseph , Howard Jason , Lacap-Bugler Donnabella , Le Lec Marissa , Lin Xiao Xiao , Lofgren Lotus , Mackay John , Meis Jacques , Morelli Kaesi A. , Perrott John , Petterson Megan , Quinones-Mateu Miguel , Rhodes Johanna , Roberts Joanna , Stajich Jason , Taylor Michael W. , Tebbutt Scott J. , Truter-Meyer Amber , Uddstrom Lydia , Urban Lara , van Rhijn Norman , Vercoe Deidre , Vesely Elisa , Weir Bevan S. , West Annie G. , Winter David J. , Yeung Juliana , Taylor Michael W. 
Published: September 2022

Abstract
Background
The critically endangered kākāpō is a flightless, nocturnal parrot endemic to Aotearoa New Zealand. Recent efforts to describe the gastrointestinal microbial community of this threatened herbivore revealed a low-diversity microbiota that is often dominated by Escherichia-Shigella bacteria. Given the importance of associated microbial communities to animal health, and increasing appreciation of their potential relevance to threatened species conservation, we sought to better understand the development of this unusual gut microbiota profile. To this end, we conducted a longitudinal analysis of faecal material collected from kākāpō chicks during the 2019 breeding season, in addition to associated nest litter material.

Results
Using an experimental approach rarely seen in studies of threatened species microbiota, we evaluated the impact of a regular conservation practice on the developing kākāpō microbiota, namely the removal of faecal material from nests. Artificially removing chick faeces from nests had negligible impact on bacterial community diversity for either chicks or nests (p > 0.05). However, the gut microbiota did change significantly over time as chick age increased (p < 0.01), with an increasing relative abundance of Escherichia-Shigella coli over the study period and similar observations for the associated nest litter microbiota (p < 0.01). Supplementary feeding substantially altered gut bacterial diversity of kākāpō chicks (p < 0.01), characterised by a significant increase in Lactobacillus bacteria.

Conclusions
Overall, chick age and hand rearing conditions had the most marked impact on faecal bacterial communities. Similarly, the surrounding nest litter microbiota changed significantly over time since a kākāpō chick was first placed in the nest, though we found no evidence that removal of faecal material influenced the bacterial communities of either litter or faecal samples. Taken together, these observations will inform ongoing conservation and management of this most enigmatic of bird species.
A one health approach to plant health
Authors: Hoffmann Vivian , Paul Birthe , Falade Titilayo , Moodley Arshnee , Ramankutty Navin , Olawoye Janice , Djouaka Rousseau , Lekei Elikana , de Haan Nicoline , Ballantyne Peter , Waage Jeff 
Published: September 2022

AbstractOne Health has been defined as an approach to the pursuit of public health and well-being that recognizes the interconnections between people, animals, plants, and their shared environment. In this opinion piece, based on a webinar of the same name, we argue that a One Health perspective can help optimize net benefits from plant protection, realizing food security and nutrition gains while minimizing unintentional negative impacts of plant health practices on people, animals and ecosystems. We focus on two primary trade-offs that lie at the interface of plant health with animal, ecosystem, and human health: protecting plant health through use of agrochemicals versus minimizing risks to human health and antimicrobial and insecticide resistance; and ensuring food security by prioritizing the health of crops to maximize agricultural production versus protecting environmental systems critical for human health. We discuss challenges and opportunities for advancement associated with each of these, taking into account how the priorities and constraints of stakeholders may vary by gender, and argue that building the capacity of regulatory bodies in low- and middle-income countries to conduct cost–benefit analysis has the potential to improve decision-making in the context of these and other multi-dimensional trade-offs.
Entrenching Inequity, Eroding Democracy: State Preemption of Local Housing Policy
Authors: Michener Jamila 
Published: September 2022

AbstractHousing is a fundamental right and a vital determinant of health. Health equity is not possible without widespread access to safe, affordable, high-quality housing. Local housing policy is a central conduit for advancing such ends. However, preemption of local law is a powerful institutional mechanism that state legislatures sometimes deploy to inhibit or nullify municipal efforts to address housing-based inequities. Local housing policies often have high stakes, are ideologically laden, and are politically salient. This makes them a clear target for preemptive action. Political science research to date has focused on broadly explaining the causes of preemption, with scant emphasis on its consequences and minimal attention to the implications for racial and economic equity. This article highlights the political repercussions of state preemption. Drawing on in-depth qualitative interviews, the article examines how local tenant organizations that work to build power within racially and economically marginalized communities perceive and respond to state preemption. The findings demonstrate how both the reality and the threat of state preemption prompt tenant organizations to adjust (and often minimize) their policy goals and to adapt their political strategies in ways that strain their capacity. By burdening local organizations that are crucial power resources in marginalized communities, state preemption of local housing policy risks entrenching inequity and eroding democracy.
County-Level Segregation and Racial Disparities in COVID-19 Outcomes
Authors: Trounstine Jessica , Goldman-Mellor Sidra 
Published: September 2022

AbstractContext: Segregation has been linked to unequal life chances. Individuals from marginalized communities experience more crime, higher levels of poverty, poorer health, and less civic engagement. In addition, segregated metropolitan regions have been found to display inequality in access to basic services. This article builds on these findings by linking segregation to infection and deaths from COVID-19.Methods: Using census data matched to COVID infection and death statistics at the county level, this article offers a theoretical basis for the researchers' choice of segregation measures and predictions for different racial groups. It analyzes the relationship between two dimensions of segregation—racial isolation and racial unevenness—and COVID outcomes for different racial and ethnic groups.Findings: In counties where Black and Latino residents lived in more racially isolated neighborhoods, they were much more likely to contract COVID-19. This pattern was exacerbated in counties with a high proportion of frontline workers. In addition, racial segregation increased COVID-19 death rates for Black, Latino, and white residents.Conclusions: These findings suggest that devastating outcomes of the coronavirus pandemic were linked to a long history of racial marginalization and entrenched discrimination produced by structural inequalities embedded in our geographies. This knowledge should be used to inform public health planning.
The Political Economy of Market Power in Pharmaceuticals
Authors: Kapczynski Amy 
Published: September 2022

AbstractThe pharmaceutical industry is among the most politically powerful business sectors in the United States today. This article describes how this industry has successfully entrenched its power, with attention to four sources of power: property power, vertical power over politics, ideational power, and material power. Attempts to reform the industry must grapple with these forms of power, which are not easily separated and which, in the current environment, tend to reinforce one another.
Study of bypassing Microsoft Windows Security using the MITRE CALDERA Framework
Authors: Mohamed Nachaat 
Published: September 2022

Background: Microsoft Windows Security is a recently implemented safeguard for the Windows operating systems, including the latest versions of Windows10 and 11. However, there is a major shortcoming in this system to stop Advanced Persistent Threat (APT). These are government-financed groups that are funded to attack other government entities. Following the initial security breach, the hacked Windows device is used to access the rest of the network devices in order to transfer data to external storage (Exfiltration). Methods: In this work, we have tested the Microsoft Windows Security system using MITRE CALDERA and ATT&CK frameworks and explain how APT groups are able to bypass Windows Security. Results: In this study we used "54ndc47" agent through GoLang feature in MITRE CALDERA platform to test and bypass Microsoft Windows Security systems (MS Windows 10). Through it, we were able to bypass the Windows Security system and display entire files in the victim's device. Conclusions: In this paper, we have provided recommendations to Microsoft to improve their Windows Security tool through the use of Artificial intelligence (AI).
Parents’ perceptions on policies of early childhood care and education programmes in selected states of Malaysia
Authors: Tang Dandan , Peng Chew Fong , Abdul Rahman MohdNazri , Dhamotharan Mogana 
Published: September 2022

Background: The 2030 agenda for sustainable development proposed global equitable quality education and lifelong learning opportunities for all children. The quality of early childhood care and education (ECCE) programs helps shape children’s minds, attitudes and behaviors, and has short and long-term effects on a child, a family and a country. In Malaysia, the government has formulated some policies and laws to protect children’s rights. However, ECCE is facing some challenges. The purpose of this study is to investigate parents’ perceptions of the quality of ECCE programs implemented by Malaysian government. Methods: A mixed method was used to collect data on parents’ perceptions of ECCE policies in selected states in Malaysia. The questionnaires, (P1/POL) from the research project “Development of a Comprehensive and Integrated Model of Quality Malaysian ECCE”, were distributed among 629 respondents who have a child in a preschool, and 22 participants were randomly selected to take part in five focus group interviews Results: The key findings of the study revealed 68% parents were not familiar with ECCE Malaysian government policy, however 84.3% stressed it is important for the government to educate them about ECCE. Thus findings indicated that the majority of parents lack awareness of the ECCE policies and quality of early childhood care and education programs related to the policies remain the issue. While interviewing the focus group ,most of them were not aware of ECCE and pointed out parents are stressing children’s academic learning in particular preschools. Conclusions: It is concluded that parents’ awareness regarding the ECCE program must be part of the policies and needs to improve. It is recommended that the government of Malaysia should supply more information on ECCE policies to parents and focus on policy implementation. Moreover, the quality of ECCE programs should be improved based on the parents’ perceptions.
Machine learning-based heart attack prediction: A symptomatic heart attack prediction method and exploratory analysis
Authors: Nandal Neha , Goel Lipika , TANWAR ROHIT 
Published: September 2022

Background; Heart attack prediction is one of the serious causes of morbidity in the world’s population. The clinical data analysis includes a very crucial disease i.e., cardiovascular disease as one of the most important sections for the prediction. Data Science and machine learning (ML) can be very helpful in the prediction of heart attacks in which different risk factors like high blood pressure, high cholesterol, abnormal pulse rate, diabetes, etc... can be considered. The objective of this study is to optimize the prediction of heart disease using ML. Methods: In this paper, we are presenting a machine learning-based heart attack prediction (ML-HAP) method in which the analysis of different risk factors and prediction for heart attacks is done using ML approaches of Support Vector Machines, Logistic Regression, Naïve Bayes and XGBoost. The data of heart disease symptoms has been collected from the UCI ML Repository and analysis has been performed on the data using ML methods. The focus has been on optimizing the prediction on the basis of different parameters. Results: XGBoost provided the best prediction among the four. The Area under the curve achieved with XGBoost is .94 and Logistic Regression is .92. The prediction with ML models in identifying heart attack symptoms is highly efficient, especially with boosting algorithms. The prediction was done to evaluate accuracy, precision, recall, and area under the curve. ML models are being trained to perform optimized predictions. Conclusions: This prediction can help clinically in analyzing the risk factors of the disease and interpretation of the patient scenario. Boosting the algorithm provided promising results to predict symptoms of heart disease. It can further be optimized by working further on risk factors associated with this condition.
Prevalence and correlates of neurocognitive impairment and psychiatric disorders among schoolchildren in Wakiso District, Uganda: a cross-sectional study
Authors: Nampijja Margaret , Sembajjwe Wilber , Mpairwe Harriet , Mpango Richard , Kinyanda Eugene 
Published: September 2022

Background: There is limited data on the burden of mental disorders among children in the general population in Africa. We examined the prevalence and correlates of neurocognitive and psychiatric disorders among schoolchildren in Uganda. Methods: This cross-sectional study enrolled 322 schoolchildren aged 5-17years in Wakiso, Uganda. We assessed for neurocognitive impairment using the Kaufmann-Assessment-Battery, and psychiatric disorders (major-depressive-disorder (MDD), attention-deficit-hyperactivity-disorder (ADHD), generalised-anxiety-disorder (GAD), and substance-use-disorder (SUD)) using the parent version of the Child and Adolescent Symptom Inventory-5, and Youth Inventory-4R Self Report. Prevalence and risk factors were determined using respectively descriptive statistics, and univariable and multivariable logistic regression. Results: Twenty-five participants (8%) had neurocognitive impairment. Nineteen (5.9%) participants had MDD, nine (2.8%) had ADHD, seven (2.2%) had GAD, 14 (8.6%) had SUD; and 30 (9.3%) had any psychiatric disorder. Among the exposure variables examined in this study, including asthma, age, sex, grade of schooling, type of school and maternal and father’s education and family socio-economic status, only asthma was associated with the disorders (MDD). Conclusions: The relatively high burden of mental disorders in this general population of children warrants targeted screening of those at risk, and treatment of those affected. Further, future studies should extensively investigate the factors that underlie the identified psychiatric disorders in this and similar general populations.
Technical Note—Bidding in Multidimensional Auctions When the Qualities of All Bidders Matter
Authors: Lorentziadis Panos L. 
Published: September 2022

Measuring the “True” Quality by Rival Bidder Qualities in Score Auctions In a procurement auction, where price and quality are evaluated by a score, the assessment criteria partially account for the “true” quality offered. The joint information of all the bids can increase the reliability of the measurement process of quality, giving better accuracy of estimation compared with the reported quality. In “Technical Note―Bidding in Multidimensional Auctions When the Qualities of All Bidders Matter,” Lorentziadis examines auctions where the score is adjusted by the qualities of all bidders, who exhibit different production efficiencies and additive separable costs. At equilibrium, the total procurement cost remains the same in the first-score and the second-score auctions. For different adjustments of the score—for example, using a weighted average of all the qualities—we find that the standard unadjusted score auction brings the highest total project cost to the buyer. Procurement managers should give consideration to score rules that account for all bidder qualities.