bluuebunny/crossref_metadata_2025 huggingface dataset:
Natural resource dependence, policy and institutions for environmental sustainability and African welfare
Authors: Mpuure Desmond Mbe‐Nyire , Mengba Jennifer Dokbila
Published: September 2023

In developing countries, particularly in Africa, dependence on natural resources poses a threat to development, leading to poor health, reduced productivity, and increased poverty among nations. This raises significant concerns for the prospects and welfare of Africa, given the rising environmental pollution. However, the literature on the mitigating effect of policies and institutions for environmental sustainability (PIES) on resource‐dependent countries in Africa is scarce. As a result, this study explores the effects of natural resource dependence and the mediating effect of PIES on under‐five mortality and human development in Africa. This novel hypothesis may contribute to the divergent differences in African welfare. Using a panel of 30 resource‐dependent countries spanning 2005 to 2021 and employing the two‐step dynamic generalized method of moments, the study provides evidence in support of the novel hypothesis. The findings show that dependence on natural resources can be either a blessing or a curse for African countries, depending on the degree to which environmental sustainability is embraced. Furthermore, a heterogeneous analysis demonstrates significant support for countries with high policies and institutions for environmental sustainability in mitigating the negative impacts of natural resource dependence on welfare. The study concludes that dependence on natural resources without environmental sustainability cannot guarantee a balance between the well‐being of the economy and the environment. Therefore, environmental management should not be politically motivated so as to sustainably improve human well‐ being in Africa.
Polyvinyl Pyrrolidone Induced “Confinement Effect” on PbI2 and the Improvement on Crystallization and Thermal Stability of Perovskite
Authors: Yu Xi , Fang Zhenxing , Lin Siyuan , Wu Shuyue , Fang Mei , Xie Haipeng , Kong Deming , Zhou Conghua
Published: September 2023

Polyvinyl pyrrolidone is blended in PbI2 with varied concentration, so as to study the coarsening dynamics of perovskite during the two‐step growth method. It is observed that polyvinyl pyrrolidone hinders the crystallization of PbI2 and helps to form a more amorphous PbI2 matrix, which then improves perovskite crystallization. As the blending concentration increases from 0 to 2 mM, average crystallite/grain size of perovskite increases from 40.29 nm/0.79 µm to 84.35 nm/1.02 µm while surface fluctuation decreases slightly from 25.64 to 23.96 nm. The observations are caused by the “confinement effect” brought by polyvinyl pyrrolidone on PbI2. Elevating blending concentration of polyvinyl pyrrolidone results in smaller PbI2 crystallites and more amorphous PbI2 matrix, thus reducing the diffusion/reaction barrier between PbI2 and organic salt and favoring perovskite crystallization. As blending concentration increases from 0 to 2 mM, the device efficiency rises from 19.76 (± 0.60) % to 20.50 (± 0.89) %, with the optimized value up to 22.05%, which is further improved to 24.48% after n‐Octylammonium iodide (OAI)‐basing surface modification. The study enlarges the scope of “confinement effect” brought by polymer molecules, which is beneficial for efficient and stable perovskite solar cell fabrication.
3D‐Printed Biomimetic Structural Colors
Authors: Bi Ran , Li Xiaohong , Ou Xingcheng , Huang Jiaqi , Huang Dantong , Chen Guoliang , Sheng Yu , Hong Wei , Wang Yan , Hu Weijie , Guo Shuang‐Zhuang
Published: September 2023

Resolution control and expansibility have always been challenges to the fabrication of structural color materials. Here, a facile strategy to print cholesteric liquid crystal elastomers (CLCEs) into complex structural color patterns with variable resolution and enhanced expansibility is reported. A volatile solvent is introduced into the synthesized CLC oligomers, modifying its rheological properties and allowing direct‐ink‐writing (DIW) under mild conditions. The combination of printing shear flow and anisotropic deswelling of ink drives the CLC molecules into an ordered cholesteric arrangement. The authors meticulously investigate the influence of printing parameters to achieve resolution control over a wide range, allowing for the printing of multi‐sized 1D or 2D patterns with constant quality. Furthermore, such solvent‐cast direct‐ink‐writing (DIW) strategy is highly expandable and can be integrated easily into the DIW of bionic robots. Multi‐responsive bionic butterfly and flower are printed with biomimetic in both locomotion and coloration. Such designs dramatically reduced the processing difficulty of precise full‐color printing and expanded the capability of structural color materials to collaborate with other systems.
Energy‐efficient organic photoelectric synaptic transistors with environment‐friendly CuInSe2 quantum dots for broadband neuromorphic computing
Authors: Zhang Junyao , Guo Ziyi , Sun Tongrui , Guo Pu , Liu Xu , Gao Huaiyu , Dai Shilei , Xiong Lize , Huang Jia
Published: September 2023

Photoelectric synaptic device is a promising candidate component in brain‐inspired high‐efficiency neuromorphic computing systems. Implementing neuromorphic computing with broad bandwidth is, however, challenging owing to the difficulty in realizing broadband characteristics with available photoelectric synaptic devices. Herein, taking advantage of the type‐II heterostructure formed between environmentally friendly CuInSe2 quantum dots and organic semiconductor, broadband photoelectric synaptic transistors (BPSTs) that can convert light signals ranging from ultraviolet (UV) to near‐infrared (NIR) into post‐synaptic currents are demonstrated. Essential synaptic functions, such as pair‐pulse facilitation, the modulation of memory level, long‐term potentiation/depression transition, dynamic filtering, and learning‐experience behavior, are well emulated. More significantly, benefitting from broadband responses, information processing functions, including arithmetic computing and pattern recognition can also be simulated in a broadband spectral range from UV to NIR. Furthermore, the BPSTs exhibit obvious synaptic responses even at an ultralow operating voltage of −0.1 mV with an ultralow energy consumption of 75 aJ per event, and show their potential in flexible electronics. This study presents a pathway toward the future construction of brain‐inspired neural networks for high‐bandwidth neuromorphic computing utilizing energy‐efficient broadband photoelectric devices.
Developing and validating an Next Generation Science Standards‐aligned construct map for chemical bonding from the energy and force perspective
Authors: Kaldaras Leonora , Akaeze Hope O. , Krajcik Joseph
Published: September 2023

Chemical bonding is central to explaining many phenomena. Research in chemical education and the Framework for K–12 Science Education (the Framework) argue for new approaches to learning chemical bonding grounded in (1) using ideas of the balance of electric forces and energy minimization to explain bond formation, (2) using learning progressions (LPs) grounded in these ideas to support learning, and (3) engaging students in 3D learning reflected in integrating the three dimensions of scientific knowledge to make sense of phenomena. The dimensions include disciplinary core ideas, scientific and engineering practices, and crosscutting concepts. While the Framework describes the theoretical basis of 3D learning, empirical evidence for the development and validation of LPs for 3D learning is limited. This work addresses that issue for the topic of chemical bonding. We develop and validate a 3D construct map for chemical bonding grounded in the idea of balance of electric forces and energy minimization. A construct map represents a finer‐grained LP spanning a shorter period and focusing on specific aspects of a larger‐scale LP. An NGSS‐aligned validated 3D LP has never been reported for the topic of chemical bonding. The LP is based on data from 9th grade Mid‐Western and Western students who used the NGSS‐aligned curriculum. Multiple validity evidence sources, including interview and item response theory analysis using an assessment tool developed to probe the 3D construct map levels, were used. We demonstrate the feasibility of using the assessment tool for assigning levels to individuals and groups of learners, which is essential for the practical applicability of the 3D construct map and provides teachers with information on how to promote learning. We hope that the 3D LP presented here will serve as a guide to develop instructional and assessment approaches for chemical bonding grounded in the fundamental scientific principles and aligned to NGSS.
Optimizing contrast protocol for bone‐subtraction CT angiography of intracranial arteries in normal dogs using 160‐slice CT
Authors: An Soyon , Hwang Gunha , Kim Rakhoon , Cha Jihye , Lee Hee Chun , Hwang Tae‐Sung
Published: September 2023

Background

Bone‐subtraction computed tomography angiography (CTA) (BSCTA) is a new technique designed to overcome the limitation of three‐dimensional CTA, where the vessels surrounded by bone and calcification can be obscured. An optimal contrast CT protocol for intracranial artery visualization with BSCTA has yet to be established in dogs.

Objectives

The purpose of this study was to determine the optimal contrast protocol of CTA for visualizing intracranial artery using an automatic bone‐subtraction technique in dogs.

Methods

Brain CTA was performed four times for each of nine healthy beagle dogs to cover all the contrast protocols: two different contrast iodine concentrations (300 and 370 mgI/mL) and two different contrast media injection rates (2 and 4 mL/s). Bone removal post‐processing was performed automatically by subtracting the non‐enhanced CT data from the contrast CT data using a dedicated workstation. The bone‐subtracted intracranial vessels were analysed for quantitative and qualitative evaluation.

Results

Quantitative evaluation showed significantly higher CT attenuation values for the group with a 370 mgI/mL iodine content at a rate of 4 mL/s than the two groups with a 300 mgI/mL iodine content at the rates of 2 and 4 mL/s (p < 0.001). Qualitative assessment revealed significantly higher mean scores for the 370 mgI/mL groups than the 300 mgI/mL groups and significantly higher mean scores for the 4 mL/s groups than the 2 mL/s groups (p < 0.05).

Conclusions

The optimal contrast protocol for BSCTA suggests that high iodine material concentration and high injection rate should be used for strong arterial attenuation and great visualization of the intracranial arterial structure in dogs.
Encephalomyocarditis virus in a capybara (Hydrochoerus hydrochaeris)
Authors: Hill Andrew Gordon , Mackie John Thomas
Published: September 2023

Encephalomyocarditis virus is responsible for epizootics and sporadic mortalities worldwide, particularly in zoos, and in non‐rodent species is characterised by sudden death due to acute myocarditis. Rodents are considered the reservoir host and show variable manifestations ranging from clinically asymptomatic infection to paralysis or death. We present a capybara (Hydrochoerus hydrochaeris) that exhibited lethargy, ataxia, nasal discharge and bradyarrhythmias over 5 days before death. Encephalomyocarditis virus infection was confirmed by histopathology, which showed non‐suppurative myocarditis with necrosis and polymerase chain reaction, and occurred despite recent vaccination.
Performance evaluation of hybrid constructed wetlands for nitrogen removal and statistical approaches
Authors: Kumar Suresh , Sangwan Vikramaditya , Kumar Munish , Shweta Shweta , Shivani Shivani , Kumar Manoj , Deswal Surinder
Published: September 2023

Nitrogen pollution in water bodies has become a pressing environmental and public health issue worldwide, demanding the implementation of effective nitrogen removal strategies. This research paper delves into the performance evaluation of hybrid constructed wetlands (HCWs) as a sustainable and innovative approach for nitrogen removal, employing a comprehensive year‐long dataset gathered from a practical setup. The study collected data under diverse operating conditions to investigate the effectiveness of HCWs in removing nitrogen. Results revealed that HCWs achieved nitrogen removal efficiencies ranging from 28% to 65%, influenced by temperature and hydraulic retention time. Optimal removal occurred at an average temperature of 28°C and a 4‐day hydraulic retention time. Notably, performance declined during colder periods, with temperatures below 15°C. The study also aims to predict nitrogen removal by three modeling techniques, that is, artificial neural networks (ANNs), support vector machines Pearson VII kernel function (SVM PUK), and multiple linear regression (MLR). Prediction has been done considering temperature (TEMP), hydraulic loading rate (HLR), initial concentration of chemical oxygen demand (COD) (CODin), initial concentration of total nitrogen (TNin), initial concentration of total phosphorous (TPin), and initial concentration of turbidity (TBin) as input parameters, whereas reduction of total nitrogen (RED TN) is regarded as output parameter. The performance of the soft computing techniques has been compared in terms of coefficient of determination (R2), root mean square error (RMSE), and mean absolute error (MAE). The analysis revealed that the performance of the SVM (PUK) model (R2: 0.572, RMSE: 0.0359, MAE: 0.0294) for the prediction of TN reduction is superior followed by MLR (R2: 0.562, RMSE: 0.0365, MAE: 0.0294) and ANN (R2: 0.597, RMSE: 0.0377, MAE: 0.0301). The present study concludes that the treated effluent by the HCWs, using water hyacinth and water lettuce, is of fair quality, thus having potential application for the treatment of rice mill wastewater in warmer climates. Further, machine learning approaches employed in estimating the total nitrogen reduction by HCWs technology have shown promising applicability and utilization in such studies.

Practitioner Points

Hybrid constructed wetlands (HCWs) are effective in removing nitrogen from wastewater.

The performance of HCWs in nitrogen removal can vary due to physical, chemical, and biological processes.

The performance of the HCWs highly depends on temperature and hydraulic retention time.

Artificial neural networks (ANNs) and support vector machines (SVMs) provided better predictions of nitrogen removal with high accuracy and low root mean square error.
Deep learning models for price forecasting of financial time series: A review of recent advancements: 2020–2022
Authors: Zhang Cheng , Sjarif Nilam Nur Amir , Ibrahim Roslina
Published: September 2023

Accurately predicting the prices of financial time series is essential and challenging for the financial sector. Owing to recent advancements in deep learning techniques, deep learning models are gradually replacing traditional statistical and machine learning models as the first choice for price forecasting tasks. This shift in model selection has led to a notable rise in research related to applying deep learning models to price forecasting, resulting in a rapid accumulation of new knowledge. Therefore, we conducted a literature review of relevant studies over the past 3 years with a view to aiding researchers and practitioners in the field. This review delves deeply into deep learning‐based forecasting models, presenting information on model architectures, practical applications, and their respective advantages and disadvantages. In particular, detailed information is provided on advanced models for price forecasting, such as Transformers, generative adversarial networks (GANs), graph neural networks (GNNs), and deep quantum neural networks (DQNNs). The present contribution also includes potential directions for future research, such as examining the effectiveness of deep learning models with complex structures for price forecasting, extending from point prediction to interval prediction using deep learning models, scrutinizing the reliability and validity of decomposition ensembles, and exploring the influence of data volume on model performance.

This article is categorized under:

Technologies > Prediction

Technologies > Artificial Intelligence
Resetting the Future: World 50.0
Authors: Landesz Tamás , Varghese Sangeeth , Sargsyan Karine
Published: September 2023

The pandemic has presented an opportunity to reflect, reimagine, and reset the world. The ancient Greeks referred to time using two different concepts: “chronos” and “kairos.” Whereas the former refers to traditional time measured by a ticking clock, the latter refers to “deep time,” when everything is possible. This book is a journey to create a community for building a better future. The WORLD 50.0 movement is working toward building a better, more inclusive, and sustainable future. Concurrently, initiatives like the United Planet (UP), Futurian, and Regenopolis are working toward a bluer, greener future by catalyzing actions needed to realize that future. The book shares the dreams of the world's top scientists, thinkers, and innovators who are continuously working on inventing the future, including transitioning to become a multi-planetary species, brain-human interfaces combined with exoskeletons, and nanomedicine reforming health care. The aim of the WORLD 50.0 movement is to build a better future together faster by crowdsourcing inputs on a global scale and engaging and scaling a community of contributors.
Future of Leadership
Authors: Landesz Tamás
Published: September 2023

The current pandemic and the accelerating future require a new type of leadership to emerge. The Young Global Leaders of the World Economic Forum (WEF) interviewed in this book envision an emerging era of humanity and empathy as we transition towards a more digital existence where global institutions will be significantly redesigned. Future leaders shall be role models, representing a new set of values that inspire new generations to lead with heart, compassion, emotional intelligence, care, education and kindness. Authentic leadership traits such as adaptability, collaboration, creativity, emotional intelligence, entrepreneurship, ethics, resilience, self-awareness and social awareness will be crucial for future-generation leaders. Eight traits responsible for the development of early leadership abilities of Young Global Leaders included evolutionary traits, early exposure to significant responsibility, high expectations, enabling environments, important crucible moments and the pursuit of passion. The concept of leadership is changing, and the right mix of authenticity and Machiavellianism is necessary to make an impact in an increasingly complex world.
Postdigital Participation in Education: A Postscript
Authors: Macgilchrist Felicitas , Weich Andreas
Published: September 2023

This postscript takes the form of a conversation between the book’s editors, who pull together the discursive strands explored in the book’s chapters in response to three guiding questions: How is the postdigital deployed in the chapters of this book? How do contemporary media constellations shape participation? And who participates how in these contemporary media constellations? Addressing these questions together, as necessitated by the intricate entanglements of the postdigital condition, the editors discuss the complexities around the term “postdigital” and the practices and implications for power relations that both influence and derive from the use of technology in education, in society, in culture, and in politics.
Visualization of Engineering Products
Authors: Ivanov Vitalii , Pavlenko Ivan , Evtuhov Artem , Trojanowska Justyna
Published: September 2023

Visualization of engineering products plays a crucial role in the design and development process. It allows engineers and designers to effectively communicate ideas, evaluate designs, identify potential issues, and make informed decisions before the physical production phase begins.
Quarks at the modular S4 cusp
Authors: de Medeiros Varzielas I. , Levy M. , Penedo J. T. , Petcov S. T.
Published: September 2023

Abstract

We analyse the possibility of describing quark masses, mixing and CP violation in $$ {S}_4^{\prime } $$

S
4
′

modular flavour models without flavons. We focus on the case where the closeness of the modulus to the point of residual $$ {\mathbb{Z}}_3^{ST} $$

ℤ
3
ST

symmetry (the cusp) plays a role in generating quark mass hierarchies and discuss the role modular form normalisations play in such constructions. We find that fitting quark data requires explicit CP breaking, unless a second modulus is introduced.
Purity of monoids and characteristic-free splittings in semigroup rings
Authors: De Stefani Alessandro , Montaño Jonathan , Núñez-Betancourt Luis
Published: September 2023

Inspired by methods in prime characteristic in commutative algebra, we introduce and study combinatorial invariants of seminormal monoids. We relate such numbers with the singularities and homological invariants of the semigroup ring associated to the monoid. Our results are characteristic independent.
Geometric Characterization of the Eyring–Kramers Formula
Authors: Avelin Benny , Julin Vesa , Viitasaari Lauri
Published: September 2023

In this paper we consider the mean transition time of an over-damped Brownian particle between local minima of a smooth potential. When the minima and saddles are non-degenerate this is in the low noise regime exactly characterized by the so called Eyring–Kramers law and gives the mean transition time as a quantity depending on the curvature of the minima and the saddle. In this paper we find an extension of the Eyring–Kramers law giving an upper bound on the mean transition time when both the minima/saddles are degenerate (flat) while at the same time covering multiple saddles at the same height. Our main contribution is a new sharp characterization of the capacity of two local minima as a ratio of two geometric quantities, i.e., the minimal cut and the geodesic distance.
The acute influence of amateur boxing on dynamic cerebral autoregulation and cerebrovascular reactivity to carbon dioxide
Authors: Wallis W. E. G. , Al-Alem Q. , Lorimer H. , Smail O. J. , Williams G. K. R. , Bond B.
Published: September 2023

Purpose

The purpose of this study was to investigate the acute effect of head impacts, sustained over the course of three rounds of amateur boxing, on indices of cerebrovascular function.

Methods

Eighteen university amateur boxers (six female) completed three experimental trials in a randomised order; (1) three rounds of boxing (BOX), (2) an equivalent bout of pad boxing (where no blows to the head were sustained; PAD), and (3) a time-matched seated control trial (CON). Indices of cerebrovascular function were determined immediately before and 45 min after each trial. Specifically, dynamic cerebral autoregulation (dCA) was determined by considering the relationship between changes in cerebral blood velocity and mean arterial pressure during 5 min of squat-stand manoeuvres at 0.05 and 0.10 Hz. Cerebrovascular reactivity was determined using serial breath holding and hyperventilation attempts.

Results

Participants received an average of 40 ± 16 punches to the head during the BOX trial. Diastolic, mean and systolic dCA phase during squat stand manoeuvres at 0.05 Hz was lower after BOX compared to pre BOX (P ≤ 0.02, effect size (d) ≥ 0.74). No other alterations in dCA outcomes were observed at 0.05 or 0.10 Hz. The number of head impacts received during the BOX trial was associated with the change in systolic phase (r = 0.50, P = 0.03). No differences in cerebrovascular reactivity to breath holding or hyperventilation were observed.

Conclusions

A typical bout of amateur boxing (i.e., three rounds) can subtly alter cerebral pressure-flow dynamics, and the magnitude of this change may be related to head impact exposure.
Metastatic lymph node ratio as an important prognostic factor in advanced gallbladder carcinoma with at least 6 lymph nodes retrieved
Authors: Wang Junke , Liu Fei , Ma Wenjie , Hu Haijie , Li Fuyu
Published: September 2023

Background

The metastatic lymph node (LN) ratio (LNR) has shown to be an important prognostic factor in various gastrointestinal malignancies. Nevertheless, the prognostic significance of LNR in gallbladder carcinoma (GBC) remains to be determined.

Methods

From January 2007 to January 2018, 144 advanced GBC patients (T2–4 stages) who underwent curative surgery with at least 6 LNs retrieved were enrolled. Receiver operating characteristic (ROC) curve was performed to identify the optimal cut-off value for LNR. The clinicopathological features stratified by LNR level were analyzed. Meanwhile, univariate and multivariate Cox regression proportional hazard models were performed to identify risk factors for overall survival (OS).

Results

The optimal cut-off point for LNR was 0.28 according to the ROC curve. LNR>0.28 was associated with higher rate of D2 LN dissection (P=0.004) and higher tumor stages (P<0.001). Extent of liver resection, extrahepatic bile duct resection, tumor stage, LNR, margin status, tumor differentiation, and perineural invasion were associated with OS in univariate analysis (all P<0.05). GBC patients with LNR≤0.28 had a significantly longer median OS compared to those with LNR>0.28 (27.5 vs 18 months, P=0.004). Multivariate analysis indicated that tumor stage (T2 vs T3/T4; hazard ratio (HR) 1.596; 95% confidence interval (CI) 1.195–2.132), LNR (≤0.28 vs >0.28; HR 0.666; 95% CI 0.463–0.958), margin status (R0 vs R1; HR 1.828; 95% CI 1.148–2.910), and tumor differentiation (poorly vs well/moderately; HR 0.670; 95% CI 0.589–0.892) were independent prognostic factors for GBC (all P<0.05).

Conclusions

LNR is correlated to advanced GBC prognosis and is a potential prognostic factor for advanced GBC with at least 6 LNs retrieved.
Detection of solidification crack formation in laser beam welding videos of sheet metal using neural networks
Authors: Huo Wenjie , Bakir Nasim , Gumenyuk Andrey , Rethmeier Michael , Wolter Katinka
Published: September 2023

Laser beam welding has become widely applied in many industrial fields in recent years. Solidification cracks remain one of the most common welding faults that can prevent a safe welded joint. In civil engineering, convolutional neural networks (CNNs) have been successfully used to detect cracks in roads and buildings by analysing images of the constructed objects. These cracks are found in static objects, whereas the generation of a welding crack is a dynamic process. Detecting the formation of cracks as early as possible is greatly important to ensure high welding quality. In this study, two end-to-end models based on long short-term memory and three-dimensional convolutional networks (3D-CNN) are proposed for automatic crack formation detection. To achieve maximum accuracy with minimal computational complexity, we progressively modify the model to find the optimal structure. The controlled tensile weldability test is conducted to generate long videos used for training and testing. The performance of the proposed models is compared with the classical neural network ResNet-18, which has been proven to be a good transfer learning model for crack detection. The results show that our models can detect the start time of crack formation earlier, while ResNet-18 only detects cracks during the propagation stage.
Quantifying the historic and future response of karst spring discharge to climate variability and change at a snow-influenced temperate catchment in central Europe
Authors: Fan Xinyang , Goeppert Nadine , Goldscheider Nico
Published: September 2023

Climate change is projected to threaten groundwater resources in many regions, but projections are highly uncertain. Quantifying the historic impact potentially allows for understanding of hydrologic changes and increases confidence in the predictions. In this study, the responses of karst discharge to historic and future climatic changes are quantified at Blautopf Spring in southern Germany, which is one of the largest karst springs in central Europe and belongs to a regional aquifer system relevant to the freshwater supply of millions of people. Statistical approaches are first adopted to quantify the hydrodynamic characteristics of the karst system and to analyse the historic time series (1952–2021) of climate variables and discharge. A reservoir model is then calibrated and evaluated with the observed discharge and used to simulate changes with three future climate-change scenarios. Results show that changes in the annual mean and annual low discharge were not significant, but the annual peak discharge shifted to a low state (<13.6 m3 s−1) from 1988 onwards due to decreasing precipitation, increasing air temperature, and less intense peak snowmelt. The peak discharge may decrease by 50% in this century according to the projections of all climate-change scenarios. Despite there being no significant historic changes, the base flow is projected to decrease by 35–55% by 2100 due to increasing evapotranspiration. These findings show the prolonged impact of climate change and variability on the floods and droughts at the springs in central Europe, and may imply water scarcity risks at similar climatic and geologic settings worldwide.
Risk factors for progression to bacteremia among patients with nosocomial carbapenem-resistant Acinetobacter baumannii pneumonia in the Intensive Care Unit
Authors: Niu Haiming , Shen Xiaoqing , Liang Hongkai , Wu Guishen , Cai Shaoqing , Shen Qian , Zhang Kouxing , Chen Miaolian , Li Jianwei
Published: September 2023

Antibiotic-resistant Acinetobacter baumannii (A. baumannii) is a common cause of hospital-acquired infections. This study aimed to identify independent factors associated with progression from nosocomial pneumonia to bacteremia in patients infected with carbapenem-resistant A. baumannii (CR-AB). From 2019 to 2021, we conducted a retrospective anaylsis of the medical records of 159 nosocomial CR-AB pneumonia patients in our Intensive Care Unit (ICU). We employed both univariate and multivariable logistic regression models to identify factors associated with the progression of nosocomial CR-AB pneumonia to bacteremia. Among the 159 patients with nosocomial CR-AB pneumonia, 40 experienced progression to bacteremia and 38 died within 28 days following diagnosis. Patients who developed bacteremia had a significantly higher 28-day mortality rate compared to those without bloodstream infection (47.50% vs. 15.97%). Multivariable logistic regression revealed that higher levels of C-Reactive protein (CRP) (OR = 1.01) and the use of continuous veno-venous hemofiltration (CVVH) treatment (OR = 2.93) were independently associated with an elevated risk of developing bacteremia. Among patients who developed bloodstream infection, those who died within 28 days exhibited significantly higher level of interleukin-6 (IL-6), a greater frequency of antifungal drugs usage, and a longer duration of machanical ventilation compared to survivors. Furthermore, the use of antifungal drugs was the only factor that associated with 28-day mortality (OR = 4.70). In ICU patients with central venous catheters who have CR-AB pneumonia and are on mechanical ventilation, higher CRP levels and CVVH treatment are risk factors for developing bacteremia. Among patients with bacteremia, the use of antifungal drugs is associated with 28-day mortality.
Inclusion levels of tree and herbaceous legumes on nutritive quality of grass silage: results from on-farm trials
Authors: Ebro Abule , Aranguiz Adolfo Alvarez , Nemera Fekadu , Bijdevaate Lisan , Addis Haymanot , Demise Hailu , van der Lee Jan
Published: September 2023

The escalating prices of protein concentrate supplements and increasing demand for dairy products in Ethiopia call for preservation of surplus forage during the growing season, to be fed to dairy cows at time of feed shortage. The objective of this on-farm study was to evaluate the nutritive quality of Napier and Desho grass silages with tree legume (sesbania) and herbaceous legumes (alfalfa, lablab, and faba bean) as legume components. Napier or Desho grasses were ensiled in bags with each legume at 0, 20, 30 and 40% inclusion levels (fresh weight). Replicates included nine and six farms in Mecha and Ad’aa districts, respectively. Silage bags were opened after 60 days, samples were taken for chemical analyses and evaluated for physical features. Data were analyzed using a completely randomized design in SPSS and differences among means separated using Duncan’s. Silages were firm at Mecha and fairly firm at Ada’a. No mold appeared. pH values varied from 3.94 to 4.5 and increased (p < 0.001) with increasing levels of legume inclusion. The crude protein values followed a similar pattern to that of the pH. The fiber contents, NDF (p < 0.001) and ADF (p < 0.05/p < 0.01) declined while that of ADL increased (p < 0.001) with increasing legume inclusion levels. The different legume-based silages were assessed as highly palatable and revealed that the use of tree and herbaceous legumes can improve the nutritive quality of grasses.
Investigating 3-D Effects on Flashing Cryogenic Jets with Highly Resolved LES
Authors: Gärtner Jan Wilhelm , Kronenburg Andreas , Rees Andreas , Oschwald Michael
Published: September 2023

For the development of upper stage rocket engines with laser ignition, the transition of oxidizer and fuel from the pure cryogenic liquid streams to an ignitable mixture needs to be better understood. Due to the near vacuum conditions that are present at high altitudes and in space, the injected fuel rapidly atomizes in a so-called flash boiling process. To investigate the behavior of flashing cryogenic jets under the relevant conditions, experiments of liquid nitrogen have been performed at the DLR Lampoldshausen. The experiments are accompanied by a series of computer simulations and here we use a highly resolved LES to identify 3D effects and to better interpret results from the experiments and existing 2D RANS. It is observed that the vapor generation inside the injector and the evolution of the spray in the combustion chamber differ significantly between the two simulation types due to missing 3D effects and the difference in resolution of turbulent structures. Still, the observed 3D spray dynamics suggest a suitable location for laser ignition that could be found in regions of relative low velocity and therefore expected low strain rates. Further, measured droplet velocities are compared to the velocities of notional Lagrangian particles with similar inertia as the measured droplets. Good agreement between experiments and simulations exists and strong correlation between droplet size and velocity can be demonstrated.
B7-H3 at the crossroads between tumor plasticity and colorectal cancer progression: a potential target for therapeutic intervention
Authors: Varghese Elizabeth , Samuel Samson Mathews , Brockmueller Aranka , Shakibaei Mehdi , Kubatka Peter , Büsselberg Dietrich
Published: September 2023

B7-H3 (B7 homology 3 protein) is an important transmembrane immunoregulatory protein expressed in immune cells, antigen-presenting cells, and tumor cells. Studies reveal a multifaceted role of B7-H3 in tumor progression by modulating various cancer hallmarks involving angiogenesis, immune evasion, and tumor microenvironment, and it is also a promising candidate for cancer immunotherapy. In colorectal cancer (CRC), B7-H3 has been associated with various aspects of disease progression, such as evasion of tumor immune surveillance, tumor-node metastasis, and poor prognosis. Strategies to block or interfere with B7-H3 in its immunological and non-immunological functions are under investigation. In this study, we explore the role of B7-H3 in tumor plasticity, emphasizing tumor glucose metabolism, angiogenesis, epithelial-mesenchymal transition, cancer stem cells, apoptosis, and changing immune signatures in the tumor immune landscape. We discuss how B7-H3-induced tumor plasticity contributes to immune evasion, metastasis, and therapy resistance. Furthermore, we delve into the most recent advancements in targeting B7-H3-based tumor immunotherapy as a potential approach to CRC treatment.
Linearly convergent bilevel optimization with single-step inner methods
Authors: Suonperä Ensio , Valkonen Tuomo
Published: September 2023

We propose a new approach to solving bilevel optimization problems, intermediate between solving full-system optimality conditions with a Newton-type approach, and treating the inner problem as an implicit function. The overall idea is to solve the full-system optimality conditions, but to precondition them to alternate between taking steps of simple conventional methods for the inner problem, the adjoint equation, and the outer problem. While the inner objective has to be smooth, the outer objective may be nonsmooth subject to a prox-contractivity condition. We prove linear convergence of the approach for combinations of gradient descent and forward-backward splitting with exact and inexact solution of the adjoint equation. We demonstrate good performance on learning the regularization parameter for anisotropic total variation image denoising, and the convolution kernel for image deconvolution.
Complex Systems Modeling of Community Inclusion Currencies
Authors: Clark Andrew , Mihailov Alexander , Zargham Michael
Published: September 2023

This interdisciplinary paper blends knowledge from computer science and economics in proposing a complex dynamic system subpopulation model for a blockchain form of local complementary currency, generic to the Grassroots Economics Foundation’s Community Inclusion Currency (CIC) implemented in Kenya. Our contribution to the emerging economics literature is five-fold: (i) we take a novel meso-economic approach to elicit utility from actual transactions data and reveal an ‘optimal’ disaggregation number of typical community subgroups; (ii) we relate the local CIC functioning to a nation-wide currency board monetary regime to argue that such a credible CIC implementation ensures trust in the CIC and makes it a valuable market-based channel to alleviate poverty, in addition to humanitarian or government aid channels. However, (iii) we also find evidence in our data that substitutes for real-world money such as CICs are perceived as inferior, and hence CIC systems can only be transitional. Then, (iv) we reveal that, for a poor population, saving dominates as a use of a cluster’s CIC balance, accounting for 47%, followed by purchase of food and water, 25%. Despite these dominant patterns, (v) we uncover a considerable heterogeneity in CIC spending behavior. Our contribution to the related computer-science and Tokenomics literature is two-fold: (i) we provide an open-source scaffold for modeling CIC viability and net flows; (ii) to simulate a subpopulation mixing process, we employ a network-based dynamical system modeling approach that is better grounded in economic principles and monetary theory.
Of causes and symptoms: using monitoring data and expert knowledge to diagnose the causes of stream degradation
Authors: Rettig Katharina , Semmler-Elpers Renate , Brettschneider Denise , Hering Daniel , Feld Christian K.
Published: September 2023

Ecological status assessment under the European Water Framework Directive (WFD) often integrates the impact of multiple stressors into a single index value. This hampers the identification of individual stressors being responsible for status deterioration. As a consequence, management measures are often disentangled from assessment results. To close this gap and to support river basin managers in the diagnosis of stressors, we linked numerous macroinvertebrate assessment metrics and one diatom index with potential causes of ecological deterioration through Bayesian belief networks (BBNs). The BBNs were informed by WFD monitoring data as well as regular consultation with experts and allow to estimate the probabilities of individual degradation causes based upon a selection of biological metrics. Macroinvertebrate metrics were shown to be stronger linked to hydromorphological conditions and land use than to water quality-related parameters (e.g., thermal and nutrient pollution). The modeled probabilities also allow to order the potential causes of degradation hierarchically. The comparison of assessment metrics showed that compositional and trait-based community metrics performed equally well in the diagnosis. The testing of the BBNs by experts resulted in an agreement between model output and expert opinion of 17–92% for individual stressors. Overall, the expert-based validation confirmed a good diagnostic potential of the BBNs; on average 80% of the diagnosed causes were in agreement with expert judgement. We conclude that diagnostic BBNs can assist the identification of causes of stream and river degradation and thereby inform the derivation of appropriate management decisions.
Can we all be Denmark? The role of civic attitudes in welfare state reforms
Authors: Celico Andrea , Rode Martin
Published: September 2023

Research has demonstrated the economic effectiveness of welfare state reforms that follow the Danish flexicurity model, broadly specifying the combination of highly flexible labor market policies and generous protection schemes. Notwithstanding, it has also been argued that large and generous welfare states may erode civic attitudes, defined here as people’s willingness to cheat on taxes and claim transfers to which they are not entitled. Combining data from all available waves of the World Values Survey and the European Values Study with a self-constructed flexicurity index, this paper finds that welfare state reforms involving a combination of higher benefits, lower labor market regulations, and active labor market policies are not significantly associated with an erosion of civic attitudes.
Bridging Informal Reasoning and Formal Proving: The Role of Argumentation in Proof-Events
Authors: Almpani Sofia , Stefaneas Petros
Published: September 2023

This paper explores the relationship between informal reasoning, creativity in mathematics, and problem solving. It underscores the importance of environments that promote interaction, hypothesis generation, examination, refutation, derivation of new solutions, drawing conclusions, and reasoning with others, as key factors in enhancing mathematical creativity. Drawing on argumentation logic, the paper proposes a novel approach to uncover specific characteristics in the development of formalized proving using “proof-events.” Argumentation logic can offer reasoning mechanisms that facilitate these environments. This paper proposes how argumentation can be implemented to discover certain characteristics in the development of formalized proving with “proof-events”. The concept of a proof-event was introduced by Goguen who described mathematical proof as a multi-agent social event involving not only “classical” formal proofs, but also other informal proving actions such as deficient or alleged proofs. Argumentation is an integral component of the discovery process for a mathematical proof since a proof necessitates a dialogue between provers and interpreters to clarify and resolve gaps or assumptions. By formalizing proof-events through argumentation, this paper demonstrates how informal reasoning and conflicts arising during the proving process can be effectively simulated. The paper presents an extended version of the proof-events calculus, rooted in argumentation theories, and highlights the intricate relationships among proof, human reasoning, cognitive processes, creativity, and mathematical arguments.
Social Interactions in Everyday Life of Socially Anxious Adolescents: Effects on Mental State, Anxiety, and Depression
Authors: Ernst Julia , Rückert Frank , Ollmann Theresa Magdalena , Voss Catharina , Kische Hanna , Knappe Susanne , Beesdo-Baum Katja
Published: September 2023

Unfavorable interpersonal behavior in social anxiety disorder (SAD) contributes to the maintenance of the disorder and may also be related to the development of secondary depression. Since there is limited research on daily life behavior in SAD, this study aimed to describe social interaction behavior and analyze the effect of positive interactions on depression, anxiety, and mental state. Data were obtained from the Behavior and Mind Health study (11/2015–12/2016), an epidemiological cohort study of adolescents and young adults (n = 1,180, aged 14–21 years) from Dresden, Germany. Interpersonal behavior, current mental state, anxiety, and depression were assessed eight times per day over four days using smartphone-based ecological momentary assessments. The analyzed subsample consisted of n = 723 participants, comparing 12-month SAD (n = 60) and healthy controls (HC; n = 663). The interaction behavior of participants with SAD did not differ substantially from that of HC in terms of frequency of social interactions, type of interaction partner, and time spent communicating, although they reported fewer real-life interaction partners (SAD: M = 2.49, SD = 4.78; HC: M = 3.18, SD = 6.43; F(17,044) = 23.92, p < 0.001). When comparing mental state, anxiety, and depression after interactions with familiar people to no interaction, no differences were found between SAD and HC. However, interactions with unfamiliar people negatively affected depressive symptoms in individuals with SAD (b = 0.53; SE = 0.25; 95%CI: 0.04–1.03; p = 0.036). In adolescents with SAD, social situations with unfamiliar people seem to be processed in a dysfunctional way, contributing to increased depressive mood in everyday life. This is particularly interesting given the high rate of secondary depression in SAD.
With a Little Help from My Friends: Profiles of Perceived Social Support and Their Associations with Adolescent Mental Health
Authors: Petersen Kimberly J. , Qualter Pamela , Humphrey Neil , Damsgaard Mogens Trab , Madsen Katrine Rich
Published: September 2023

This study investigated profiles of perceived social support and their associations with mental health indicators for male and female adolescents. The sample was a nationally representative group of Danish adolescents age 13–16 years (Male N = 1114; Female N = 1065). Latent profile analysis was used to identify profiles of perceived social support from different sources (classmate, teacher, family, friend). Three distinct profiles of perceived social support were identified for both genders: ‘High’ support from all sources (54.4% of males; 55.5% of females), ‘Moderate’ support from all sources (31.6% of males; 28.8% of females) and ‘Low friend’ support with moderate support from other sources (13.9% of males; 15.7% of females). The ‘high’ perceived support profile was associated with optimal mental health; the ‘moderate’ perceived support profile was associated with lower wellbeing and more frequent emotional symptoms; and the ‘low friend’ perceived support profile was associated with the lowest levels of wellbeing and, specifically for females, higher frequency of emotional symptoms. Results highlight typical profiles of perceived social support among adolescents, and demonstrate nuanced associations between perceived social support and mental health indicators, with notable gender differences.