bluuebunny/crossref_metadata_2025_split huggingface dataset:
Incidence and predictors of complications in Gram-negative bloodstream infection
Authors: Mondal Utpal , Warren Erin , Bookstaver P. Brandon , Kohn Joseph , Al-Hasan Majdi N. 
Published: March 2024

Abstract
Background
The incidence of metastatic complications in Gram-negative bloodstream infection (GN-BSI) remains undefined. This retrospective cohort study examines the incidence and predictors of complications within 90 days of GN-BSI.

Methods
Patients with GN-BSIs hospitalized at two Prisma Health-Midlands hospitals in Columbia, South Carolina, USA from 1 January 2012 through 30 June 2015 were included. Complications of GN-BSI included endocarditis, septic arthritis, osteomyelitis, spinal infections, deep-seated abscesses, and recurrent GN-BSI. Kaplan–Meier analysis and multivariate Cox proportional hazards regression were used to examine incidence and risk factors of complications, respectively.

Results
Among 752 patients with GN-BSI, median age was 66 years and 380 (50.5%) were women. The urinary tract was the most common source of GN-BSI (378; 50.3%) and Escherichia coli was the most common bacteria (375; 49.9%). Overall, 13.9% of patients developed complications within 90 days of GN-BSI. The median time to identification of these complications was 5.2 days from initial GN-BSI. Independent risk factors for complications were presence of indwelling prosthetic material (hazards ratio [HR] 1.73, 95% confidence intervals [CI] 1.08–2.78), injection drug use (HR 6.84, 95% CI 1.63–28.74), non-urinary source (HR 1.98, 95% CI 1.18–3.23), BSI due to S. marcescens, P. mirabilis or P. aeruginosa (HR 1.78, 95% CI 1.05–3.03), early clinical failure criteria (HR 1.19 per point, 95% CI 1.03–1.36), and persistent GN-BSI (HR 2.97, 95% CI 1.26–6.99).

Conclusions
Complications of GN-BSI are relatively common and may be predicted based on initial clinical response to antimicrobial therapy, follow-up blood culture results, and other host and microbiological factors.
Sentinel node biopsy in gynaecological cancers: state of art and future perspectives
Authors: Fuoco Valentina , Sassano Serena , Fragomeni Simona M. , Bizzarri Nicolò , Arciuolo Damiano , Bruno Isabella , Di Giuda Daniela , Collarino Angela 
Published: March 2024

Abstract
Purpose
This review aims to provide an overview of current knowledge and future perspectives on sentinel node biopsy in gynaecological cancers.

Methods
Literature research in the PubMed/MEDLINE database was carried out to identify relevant studies on sentinel node biopsy in gynaecological cancers. We selected only original studies, published in the English language and including a minimum of nine patients.

Results
The most relevant results on sentinel node biopsy in gynaecological cancers were summed up, focusing on clinical indications, technical aspects, preoperative and intraoperative procedures and the latest technological advances.

Conclusion
Sentinel node biopsy has been widely validated in well-selected patients with early-stage vulvar, cervical and endometrial cancers. It is essential to standardise the acquisition protocol, including SPECT/CT imaging, for an improved surgical planning and a personalised approach. Recent technological advances, such as hybrid tracers and intraoperative tools, may efficiently guide gynaecological cancer surgery.
Preoperative contributing factors and the remission of diabetes after metabolic surgery: the mediating role of preoperative triglyceride
Authors: Niu Lijuan , Mu Liqian , Wu Runda , Tong Shan , Mao Zhongqi , Yang Yi , Yin Jun 
Published: March 2024

Abstract
Background and objective
Limited understanding exists regarding the factors affecting the prognosis of surgical treatment for type 2 diabetes mellitus (T2DM), particularly in Chinese patients. In this study, we examined a cohort of early and intermediate obese T2DM patients to explore the potential impact of preoperative lipid metabolism in metabolic surgery on the postoperative remission of T2DM.

Methods
Participants with T2DM and obesity underwent metabolic surgery. Clinical data, including baseline body mass index, percentage of excess weight loss, and preoperative biochemical indicators, were collected and analyzed. A multidisciplinary team conducted patient follow-up. Remission was defined as sub-diabetic hyperglycemia (HbA1c < 48 mmol/mol, fasting glucose 100–125 mg/dl) without pharmacological intervention for at least 12 months.

Results
Over a median follow-up of 27 months, 96 T2DM patients with metabolic surgery were studied, with no laparotomies required. Among these patients, 61 (63.5%) achieved complete remission, and 85 (88.5%) experienced remission. In multivariable analysis models, preoperative fasting blood glucose (FBG) significantly correlated with all postoperative outcomes. Furthermore, mediation analysis indicated that preoperative triglycerides (TG) mediated 26.31% of the association between preoperative FBG and postoperative remission. Both preoperative FBG and TG were negatively associated with the postoperative remission of T2DM.

Conclusion
In summary, our findings suggest that lower preoperative fasting glucose levels enhance the likelihood of postoperative T2DM remission. Moreover, preoperative TG could potentially play a mediating role in the postoperative remission of T2DM. Therefore, evaluating and managing fasting glucose and lipids before the procedure may aid in assessing the prognosis of metabolic surgery.
Level of evidence Level III, designed cohort.
Morphological and Chemical Characteristics of Microplastics in Surface Water of the Vaal River, South Africa
Authors: Saad Dalia , Ramaremisa Gibbon , Ndlovu Michelle , Chimuka Luke 
Published: March 2024

Abstract
Microplastics research in South Africa has focused on marine and coastal areas, with limited studies reporting microplastics in freshwaters. To address this gap, we conducted this study to investigate the presence, abundance, physical characteristics, and chemical composition of microplastics in the surface water of the Vaal River, one of the most important freshwater systems in South Africa. Twenty-two surface water samples were collected along 60 km of the middle part of the river using a 55 μm plankton net. Samples were treated by acid digestion, and MPs were separated by density separation. Physical identification was performed using a Nikon stereomicroscope, and chemical composition was identified using Raman spectroscopy. MPs were observed in all samples with 0.13 to 2.52 particles/m3 concentrations. Microplastics ranged in size from 0.06 – 4.95 mm, with more than 89% less than 2 mm, and 81% were fragments (39%) and fibers (42%). Microplastics were observed in numerous colours, of which green, black, and blue were the most dominant, representing 22%, 19%, and 18%, respectively. Chemical analysis revealed the polymer types as high-density polyethylene (HDPE), polypropylene (PP), and low-density polyethylene (LDPE). In addition, two colourants, pigment yellow 83 and carbon black, were detected. This study provides new data on microplastic occurrence and characteristics in the Vaal River system and offers a baseline for future monitoring. Our findings confirm that the Vaal River is under a real threat of microplastic contamination, which could impact its role as a significant freshwater system in South Africa.

Highlights
• Microplastics were prevalent in the surface water of the Vaal River.
• Fibrous, small-sized, and coloured microplastics were most abundant.
• Polymers were identified as HDPE, LDPE, and PP.
A Molecular-Sieving Interphase Towards Low-Concentrated Aqueous Sodium-Ion Batteries
Authors: Liu Tingting , Wu Han , Wang Hao , Jiao Yiran , Du Xiaofan , Wang Jinzhi , Fu Guangying , Zhang Yaojian , Zhao Jingwen , Cui Guanglei 
Published: March 2024

AbstractAqueous sodium-ion batteries are known for poor rechargeability because of the competitive water decomposition reactions and the high electrode solubility. Improvements have been reported by salt-concentrated and organic-hybridized electrolyte designs, however, at the expense of cost and safety. Here, we report the prolonged cycling of ASIBs in routine dilute electrolytes by employing artificial electrode coatings consisting of NaX zeolite and NaOH-neutralized perfluorinated sulfonic polymer. The as-formed composite interphase exhibits a molecular-sieving effect jointly played by zeolite channels and size-shrunken ionic domains in the polymer matrix, which enables high rejection of hydrated Na+ ions while allowing fast dehydrated Na+ permeance. Applying this coating to electrode surfaces expands the electrochemical window of a practically feasible 2 mol kg–1 sodium trifluoromethanesulfonate aqueous electrolyte to 2.70 V and affords Na2MnFe(CN)6//NaTi2(PO4)3 full cells with an unprecedented cycling stability of 94.9% capacity retention after 200 cycles at 1 C. Combined with emerging electrolyte modifications, this molecular-sieving interphase brings amplified benefits in long-term operation of ASIBs.
The Use of Instagram and TikTok in Relation to Problematic Use and Well-Being
Authors: Hendrikse Calanthe , Limniou Maria 
Published: March 2024

AbstractMuch of the existing literature on the influence of social media use on well-being has focused on Facebook. Additionally, there exist inconsistencies in how different aspects of social media use (i.e., duration, problematic use, and emotional investment) impact well-being. Thus, the present study aimed to investigate how engagement with social media (Instagram and TikTok) was related to problematic social media use and mental well-being. Additionally, this study examined individuals’ emotional investment (value attributed to “likes” and social media followers) on each platform and how this related to problematic social media use and well-being. In this correlational study, 252 participants completed an online questionnaire including validated scales (e.g., the Rosenberg self-esteem scale) and items measuring the time spent on each platform (minutes per day) and the importance of likes, and followers. Time spent on TikTok was a significant positive predictor of problematic social media use, depression, and self-esteem, however, did not predict loneliness. Time spent on Instagram was a significant positive predictor of problematic social media use, but not any other well-being factors. These latter findings highlight the need to investigate additional factors related to how individuals are using social media, as duration is not a sufficient predictor of well-being. Problematic social media use was a significant positive predictor of depression and self-esteem, but not loneliness. Emotional investment varied in predicting problematic social media use and well-being across the two social media platforms. Present findings may alert clinical psychologists to the importance of monitoring social media use in clinical populations.
Acute Treatment with the Nootropic CILTEP® Does Not Improve Cognitive Performance in Healthy Middle-Aged Participants
Authors: Possemis Nina , Caldenhove Stéphanie , Sambeth Anke , Blokland Arjan 
Published: March 2024

AbstractThis study investigated the acute effects of the dietary nootropic stack CILTEP®. It contains a combination of ingredients that have been individually reported to improve cognitive performance. Especially, the ingredients luteolin, which is considered a phosphodiesterase type 4 (PDE4) inhibitor, and forskolin, an adenylate cyclase stimulator, were of interest since they can increase the second messenger cAMP and thus also intracellular signaling. Numerous studies have shown that inhibition of PDE4 can improve memory in animals and humans. We examined whether acute dosing of 3 capsules of CILTEP® would improve cognitive function in healthy participants aged 30 to 40 (n = 33). We used a randomized, double-blind, placebo-controlled, two-way cross-over design. Our test battery was aimed at measuring memory performance, attention, and sensorimotor speed. The primary outcome measures were the performance on the verbal learning task and the spatial pattern separation task. Secondary outcomes included other cognitive tests, event-related potentials (ERPs), and assessment of the activity of the enzyme beta-glucuronidase and its effect on the bioavailability of luteolin, heart rate, and blood pressure. No relevant effects of acute CILTEP® treatment were found on any measure of the test battery or ERPs. Blood plasma concentrations of luteolin increased, yet about 2000 times too low to likely exert any PDE4 inhibition. CILTEP® treatment did neither affect heart rate nor blood pressure. In summary, there is no evidence that a single standardized dose of 3 capsules of CILTEP® can improve cognitive function in healthy middle-aged participants.
A quantum algorithm for linear differential equations with layerwise parameterized quantum circuits
Authors: Xiao Junxiang , Wen Jingwei , Zhou Zengrong , Qian Ling , Huang Zhiguo , Wei Shijie , Long Guilu 
Published: March 2024

AbstractSolving linear differential equations is a common problem in almost all fields of science and engineering. Here, we present a variational algorithm with shallow circuits for solving such a problem: given an $$N \times N$$

N
×
N

matrix $${\varvec{A}}$$

A

, an N-dimensional vector $$\varvec{b}$$

b

, and an initial vector $$\varvec{x}(0)$$

x

(
0
)

, how to obtain the solution vector $$\varvec{x}(T)$$

x

(
T
)

at time T according to the constraint $$\textrm{d}\varvec{x}(t)/\textrm{d} t = {\varvec{A}}\varvec{x}(t) + \varvec{b}$$

d

x

(
t
)
/
d
t
=

A

x

(
t
)
+

b

. The core idea of the algorithm is to encode the equations into a ground state problem of the Hamiltonian, which is solved via hybrid quantum-classical methods with high fidelities. Compared with the previous works, our algorithm requires the least qubit resources and can restore the entire evolutionary process. In particular, we show its application in simulating the evolution of harmonic oscillators and dynamics of non-Hermitian systems with $$\mathcal{P}\mathcal{T}$$

P
T

-symmetry. Our algorithm framework provides a key technique for solving so many important problems whose essence is the solution of linear differential equations.
Digital ethicswashing: a systematic review and a process-perception-outcome framework
Authors: Schultz Mario D. , Conti Ludovico Giacomo , Seele Peter 
Published: March 2024

AbstractThe term “ethicswashing” was recently coined to describe the phenomenon of instrumentalising ethics by misleading communication, creating the impression of ethical Artificial Intelligence (AI), while no substantive ethical theory, argument, or application is in place or ethicists involved. Ethicswashing resembles greenwashing for environmental issues and has become an issue – particularly since 2019 with Thomas Metzinger’s harsh criticisms as a member of the EU panel for developing ethical guidelines for AI, which he called “ethicswashing.” Nowadays, increased ethics washing has changed the perception of AI ethics, leading critics to find a “trivialization” of ethics that may even lead to “ethics bashing.” Considering the scattered literature body and the various manifestations of digital ethicswashing, we recognise the need to assess the existing literature comprehensively. To fill this gap, this research systematically reviews current knowledge about digital ethicswashing stemming from various academic disciplines, contributing to an up-to-date assessment of its underlying characteristics. Applying content analysis to map the field leads us to present five thematic clusters: ethicswashing, ethics bashing, policymaking and regulation, watchdogs, and academia. In conclusion, we synthesise ethicswashing along a process-perception-outcome framework to provide future research to explore the multiple meanings of digital ethicswashing.
Opportunities, challenges, and benefits of AI innovation in government services: a review
Authors: Alhosani Khalifa , Alhashmi Saadat M. 
Published: March 2024

AbstractArtificial intelligence (AI) has emerged as an excellent tool across multiple industries and holds great promise for the government, society, and economy. However, the absence of a distinct consensus regarding the definition and scope of artificial intelligence hinders its practical implementation in government settings. This article examines the various methodologies, emphases, and goals within artificial intelligence, emphasizing its ability to enhance human capabilities in critical situations. Considering the present advantages and enhanced productivity brought about by AI adoption in trailblazing government departments, this study explores the possible benefits and limitations of AI usage in the public sector. By looking at the cross-disciplinary difficulties of public AI applications, such as language hurdles and service delays, this study highlights the necessity for a thorough knowledge of the risks, impediments, and incentives of employing AI for government services. The study hopes to provide insight into AI research's ultimate aims, including object manipulation, natural language processing, and reasoning. This study emphasizes the potential for greater productivity, simplified procedures, and reduced obligations by analyzing the pros and cons of using AI in the public sector. Further, organizational theory is considered a tool for figuring out how to deal with challenges and maximize possibilities associated with AI deployment. The theory is used as the conceptual framework to understand the benefits, opportunities, and challenges involved in using AI when providing government services. The results of this research help us better understand how AI may revolutionize public service delivery by stimulating new ideas and improving efficiency. This study covers critical questions about organizational theory's role in improving government AI adoption, the challenges governments have in adopting AI, and the potential benefits AI might offer public service delivery. The research recommends a strategic approach to AI adoption in the public sector, considering organizational, ethical, and societal implications while recognizing the possibility of AI's transformative impacts on governments' service provision.
GAIT analysis based on GENDER detection using pre-trained models and tune parameters
Authors: Vora Charmy , Katkar Vijay , Lunagaria Munindra 
Published: March 2024

AbstractIn past several decades, gait biometrics has emerged as a viable alternative to traditional identification methods, offering advancements in surveillance, monitoring, and analysis techniques. However, determining gender based on gait remains a challenge, particularly in computer vision applications. This study proposes a robust and adaptable approach to address this issue by leveraging gait analysis. There is a growing need for datasets tailored to gait analysis and recognition to facilitate the extraction of relevant data. While most existing research relies on image-based gait datasets, this study utilizes the OULP-Age dataset from OU-ISIR, representing gait through gait energy images (GEIs). The methodology involves feature extraction from GEIs using pre-trained models, followed by classification with the XGBoost classifier. Gender prediction is enhanced through parameter fine-tuning of the XGBoost classifier. Comparative analysis of 11 pre-trained models for feature extraction reveals that DenseNet models, combined with optimized XGBoost parameters, demonstrate promising results for gender prediction. This study contributes to advancing gender prediction based on gait analysis and underscores the efficacy of integrating deep learning models with traditional classifiers for improved accuracy and reliability.
New memory-one strategies of the Iterated Prisoner’s Dilemma: a new framework to programmed human-AI interaction
Authors: de Paulo Katharine Padilha , Estombelo-Montesco Carlos Alberto , Tejada Julian 
Published: March 2024

AbstractWith the rapid and continuing development of AI, the study of human-AI interaction is increasingly relevant. In this sense, we propose a reference framework to explore a model development in the context of social science to try to extract valuable information to the AI context. The model we choose was the Prisoner Dilemma using the Markov chain approach to study the evolution of memory-one strategies used in the Prisoner’s Dilemma in different agent-based simulation contexts using genetic algorithms programmed on the NetLogo environment. We developed the Multiplayer Prisoner’s Dilemma simulation from deterministic and probabilistic conditions, manipulating not only the probability of communication errors (noise) but also the probability of finding again the same agent. Our results suggest that the best strategies depend on the context of the game, following the rule: the lower the probability of finding the same agent again, the greater the chance of defect. Therefore, in environments with a low probability of interaction, the best strategies were the ‘Always Defect’ ones. But as the number of interactions increases, a different strategy emerges that is able to win Always Defect strategies, such as the Spiteful/grim. In addition, our results also highlight strategies that emerge in situations in which Spiteful/grim and Always Defect were banned. These are memory-one strategies with better performance than both TFT and PAVLOV under all conditions showing behaviors that are particularly deceiving but successful. The previously memory-one strategies for the Prisoner Dilemma represent a set of extensively tested strategies in contexts with different probability of encountering each other again and provide a framework for programming algorithms that interact with humans in PD-like trusted contexts.
Spatial pattern, and evolution of China’s urban agglomerations
Authors: Yu Taofang , Shu Tianheng , Xu Jiahui 
Published: March 2024

AbstractChina's urban agglomeration is not only crucial to tackle with the more and more contradiction between population, resources and environment, but also an important spatial actor to increase the global competitiveness and promote the transformation of China's economic development mode. In the national "14th Five-Year Plan" in 2021, it is proposed to "promote the coordinated and development of large, medium-sized and small cities and towns based on urban agglomeration and metropolitan area". Generally, 19 urban agglomerations designated in this Plan are heterogeneous in development level and national functions. To this end, from the nature of urban agglomerations, especially on agglomeration economy and functional urban region hypothesis, the research focuses on the spatial pattern and changes of these 19 areas mainly based on the 6th and 7th national census. The findings show that, China’s UAs are unique in driving forces, and spatial patterns as well. China’s UAs are more state-led, though now the marketing forces more and more crucial. The UAs have been evolved from the early planned economy period to the reform and opening up period, and then to the further development of the Socialist market economy until now. Unlike other typical UAs abroad, most of the developed UAs are more specialized in manufacture, not in producer services, though these regions show a remarkable high-end services oriented shift in 2010–2020.