bluuebunny/crossref_metadata_2025_split huggingface dataset:
Clinical analysis of patients with systemic lupus erythematosus complicated with liver failure
Authors: Zhang Lili , Yin Ling , Lv Wenliang , Wang Yitong , Liu Yang , Gou Chunyan , Hu Jianhua , Wang Xiaojun 
Published: February 2023

AbstractThe objective of this study is to analyze and summarize the characteristics of the clinical data of patients with systemic lupus erythematosus (SLE) complicated with liver failure, and to improve the cognition of the disease. The clinical data of patients with SLE complicated with liver failure hospitalized in Beijing Youan Hospital from January 2015 to December 2021 were collected retrospectively, including general information and laboratory examination data, and the clinical characteristics of the patients were summarized and analyzed. Twenty-one SLE patients with liver failure were analyzed. The diagnosis of liver involvement was earlier in 3 cases than that of SLE, and later in 2 cases. Eight patients were diagnosed with SLE and autoimmune hepatitis at the same time. The medical history is between 1 month and 30 years. This was the first case report of SLE complicated with liver failure. We found that: (1) among the 21 patients, organ cysts (liver and kidney cysts) were more common and the proportion of cholecystolithiasis and cholecystitis was higher than that in previous studies, but the proportion of renal function damage and joint involvement was lower. (2) The inflammatory reaction was more obvious in SLE patients with acute liver failure. The degree of liver function injury in SLE patients with autoimmune hepatitis was less than that in patients with other liver diseases. (3) The use of glucocorticoid in SLE patients with liver failure was worthy of further discussion.

Key Points• Patients with SLE complicated with liver failure have a lower proportion of renal impairment and joint involvement.• The study firstly reported SLE patients with liver failure.• Glucocorticoids in the treatment of SLE patients with liver failure are worthy of further discussion.
A framework for modern time geography: emphasizing diverse constraints on accessibility
Authors: Dodge Somayeh , Nelson Trisalyn A. 
Published: February 2023

AbstractTime geography is widely used by geographers as a model for understanding accessibility. Recent changes in how access is created, an increasing awareness of the need to better understand individual variability in access, and growing availability of detailed spatial and mobility data have created an opportunity to build more flexible time geography models. Our goal is to outline a research agenda for a modern time geography that allows new modes of access and a variety of data to flexibly represent the complexity of the relationship between time and access. A modern time geography is more able to nuance individual experience and creates a pathway for monitoring progress toward inclusion. We lean on the original work by Hägerstrand and the field of movement GIScience to develop both a framework and research roadmap that, if addressed, can enhance the flexibility of time geography to help ensure time geography will continue as a cornerstone of accessibility research. The proposed framework emphasizes the individual and differentiates access based on how individuals experience internal, external, and structural factors. To enhance nuanced representation of inclusion and exclusion, we propose research needs, focusing efforts on implementing flexible space–time constraints, inclusion of definitive variables, addressing mechanisms for representing and including relative variables, and addressing the need to link between individual and population scales of analysis. The accelerated digitalization of society, including availability of new forms of digital spatial data, combined with a focus on understanding how access varies across race, income, sexual identity, and physical limitations requires new consideration for how we include constraints in our studies of access. It is an exciting era for time geography and there are massive opportunities for all geographers to consider how to incorporate new realities and research priorities into time geography models, which have had a long tradition of supporting theory and implementation of accessibility research.
Navigating power imbalances in landscape governance: a network and influence analysis in southern Zambia
Authors: Siangulube Freddie S. , Ros-Tonen Mirjam A. F. , Reed James , Djoudi Houria , Gumbo Davison , Sunderland Terry 
Published: February 2023

AbstractActors engaging in integrated landscape approaches to reconciling conservation and development represent multiple sectors and scales and actors with different powers, resource access, and influence on decision-making. Despite growing acknowledgement, limited evidence exists on the implications of power relations for landscape governance. Therefore, this paper asks why and how different forms of power unfold and affect the functioning of multi-stakeholder platforms in southern Zambia. Social network analysis and a power influence assessment reveal that all actors exercise some form of visible, hidden, or invisible power in different social spaces to influence decision-making or negotiate a new social order. The intersection of customary and state governance reveals that power imbalances are the product of actors’ social belongingness, situatedness, and settlement histories. We conclude that integrated landscape approaches are potentially suited to balance power by triggering new dynamic social spaces for different power holders to engage in landscape decision-making. However, a power analysis before implementing a landscape approach helps better recognise power differentials and create a basis for marginalised actors to participate in decision-making equally. The paper bears relevance beyond the case, as the methods used to unravel power dynamics in contested landscapes are applicable across the tropics where mixed statutory and customary governance arrangements prevail.
Expert consensus on the management of chronic lymphocytic leukaemia in Asia
Authors: Tse Eric , Kwong Yok Lam , Goh Yeow Tee , Bee Ping Chong , Ng Soo Chin , Tan Daryl , Caguioa Priscilla , Nghia Huynh , Dumagay Teresita , Norasetthada Lalita , Chuncharunee Suporn , Radhakrishnan Vivek , Bagal Bhausaheb , Atmakusuma Tubagus Djumhana , Mulansari Nadia Ayu 
Published: February 2023

AbstractIn recent years, considerable progress has been made in the standard treatment for chronic lymphocytic leukaemia (CLL) due to the availability of new potent drugs. However, the majority of data on CLL were derived from Western populations, with limited studies and guidelines on the management of CLL from an Asian population perspective. This consensus guideline aims to understand treatment challenges and suggest appropriate management approaches for CLL in the Asian population and other countries with a similar socio-economic profile. The following recommendations are based on a consensus by experts and an extensive literature review and contribute towards uniform patient care in Asia.
Co-jumps and recursive preferences in portfolio choices
Authors: Oliva Immacolata , Stefani Ilaria 
Published: February 2023

AbstractThis paper investigates a multivariate, dynamic, continuous-time optimal consumption and portfolio allocation problem when the investor faces recursive utilities. The economy we are considering is described through both diffusion and discontinuities in the dynamics. We derive an approximated closed-form solution to optimal rules by exploiting standard dynamic programming techniques. Our findings are manifold. First, we obtain dynamic optimal weights, inversely proportional to volatility. Second, we show that both co-jumps frequency and intensity play a crucial role, as they considerably limit potential losses in the investors’ wealth. Third, we prove that jumps in precision reinforce the effect of jumps in price, further reducing optimal allocation. Finally, we highlight how co-jumps may influence investors’ choices regarding intertemporal consumption.
Machine learning algorithms to forecast air quality: a survey
Authors: Méndez Manuel , Merayo Mercedes G. , Núñez Manuel 
Published: February 2023

AbstractAir pollution is a risk factor for many diseases that can lead to death. Therefore, it is important to develop forecasting mechanisms that can be used by the authorities, so that they can anticipate measures when high concentrations of certain pollutants are expected in the near future. Machine Learning models, in particular, Deep Learning models, have been widely used to forecast air quality. In this paper we present a comprehensive review of the main contributions in the field during the period 2011–2021. We have searched the main scientific publications databases and, after a careful selection, we have considered a total of 155 papers. The papers are classified in terms of geographical distribution, predicted values, predictor variables, evaluation metrics and Machine Learning model.
Assessing the Departures from the Energy- and Flux-Budget (EFB) Model in Heterogeneous and Urbanized Environment for Stable Atmospheric Stratification
Authors: Trini Castelli Silvia , Mortarini Luca , Cava Daniela , Martano Paolo , Argentini Stefania , Casasanta Giampietro , Petenko Igor , Sozzi Roberto , Tampieri Francesco 
Published: February 2023

AbstractTurbulence closure schemes, besides their intrinsic theoretical importance, represent a fundamental component in the atmospheric numerical models. Among his numerous and diverse scientific contributions, Prof. Sergej S. Zilitinkevich, with his coauthors, elaborated a turbulence closure model for stably-stratified geophysical flows, the Energy and Flux Budget (EFB) model. This closure has been verified and applied on many different experimental datasets and case studies, for steady state and homogeneous conditions. Having available observational datasets for urban and suburban sites in different cities in Italy, we investigate the deviation of the observations of turbulent kinetic energy and momentum flux from the EFB turbulence closure model in heterogeneous conditions. This allows addressing and interpreting the features that induce such deviation between the model and the observations. The EFB model is then revisited including residual terms that can account for the non-stationarity and heterogeneity of the considered cases. The correction with the residual terms leads to improve the agreement between the theoretical formulations and the observed behaviour for the turbulent kinetic energy shares and for the vertical momentum flux.
How to Neutralize Primary Psychopathic Leaders’ Damaging Impact: Rules, Sanctions, and Transparency
Authors: Laurijssen L. Maxim , Wisse Barbara , Sanders Stacey , Sleebos Ed 
Published: February 2023

AbstractPrimary psychopathy in leaders, also referred to as successful psychopathy or corporate psychopathy, has been put forward as a key determinant of corporate misconduct. In contrast to the general notion that primary psychopaths’ destructiveness cannot be controlled, we posit that psychopathic leaders’ display of self-serving and abusive behavior can be restrained by organizational contextual factors. Specifically, we hypothesize that the positive relationship between leader primary psychopathy on the one hand and self-serving behavior and abusive supervision on the other will be weaker to the extent that the organizational context (clear rules and policies, sanctionability of misconduct, and transparency of behavior) is stronger. Three studies (one experiment, one survey of leader–subordinate dyads, and one survey of teams) showed that clear rules in particular weakened the positive association between leader primary psychopathic traits and their self-serving and abusive behavior. Explanations for why clear rules rein in primary psychopathic leaders’ destructive behavior more than sanctionability of misconduct and transparency of behavior will be discussed.
COLLTS: A Promising Interactive Read-Aloud Intervention for Three-Year-Old Dual-Language Learners
Authors: August Diane L. , Carlson Coleen D. , Barr Christopher D. , Bergey Rebecca 
Published: February 2023

AbstractThe goal of this pilot study was to test a bilingual interactive read-aloud intervention designed to develop the oral language proficiency of three-year-old dual language learners (DLLs). The eight-week intervention—Cultivating Oral Language and Literacy Talent in Students (COLLTS)—was aligned with the Head Start Early Learning Outcomes Framework and consisted of evidence-based instructional methods; resources for teachers and students that supported teachers in enacting these methods; professional development related to the methods and resources; and family literacy activities. Control teachers were given the same books as the treatment teachers to read to their students but were not provided with all of the professional development and any of the other COLLTS resources. The study was implemented in 22 classrooms in seven Head Start centers in a large city in the southern United States. Data were collected to assess students’ language outcomes, teacher fidelity, and family participation. Findings indicated gains on a short receptive measure of instructed vocabulary, but no significant differences between treatment and control DLLs on that measure. Findings also indicated significantly greater gains for treatment DLLs compared with control DLLs in semantic knowledge measured by oral narrative retellings coded using language sample analysis; high levels of parent involvement and family satisfaction; and significantly greater gains in student’s vocabulary knowledge for more engaged treatment families.
Patient-reported outcome measures for uncomplicated urinary tract infections in women: a systematic review
Authors: Piontek Katharina , Donhauser Theresa , Kann Gesina , Fechtner Marie , Apfelbacher Christian , Gabes Michaela 
Published: February 2023

AbstractPurposeTo conduct a systematic review of the quality of existing patient-reported outcome measures (PROMs) for use in women with uncomplicated urinary tract infections (UTIs) applying the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) methodology, and to derive recommendations for their use in future research.MethodsA systematic literature search was performed in PubMed and Web of Science. Studies reporting on the development and/or validation of any PROMs for uncomplicated UTIs in women were considered eligible. We evaluated the methodological quality of each included study using the COSMIN Risk of Bias Checklist, and further applied predefined criteria for good measurement properties. Finally, we graded the evidence and derived recommendations for the use of the included PROMs.ResultsData from 23 studies reporting on six PROMs were included. From those, the Acute Cystitis Symptom Score (ACSS) and the Urinary Tract Infection-Symptom and Impairment Questionnaire (UTI-SIQ-8) can be recommended for further use. Both instruments showed sufficient content validity. We further found high-quality evidence for sufficient internal consistency of the UTI-SIQ-8, while this criterion was not assessed for the ACSS due to a formative measurement model. All other PROMs have the potential to be recommended for use, but require further validation.ConclusionThe ACSS and the UTI-SIQ-8 have the potential to be recommended for use in women with uncomplicated UTIs in future clinical trials. For all included PROMs, further validation studies are indicated.Systematic review registration: PROSPERO.
The modal basis of scientific modelling
Authors: Tahko Tuomas E. 
Published: February 2023

AbstractThe practice of scientific modelling often resorts to hypothetical, false, idealised, targetless, partial, generalised, and other types of modelling that appear to have at least partially non-actual targets. In this paper, I will argue that we can avoid a commitment to non-actual targets by sketching a framework where models are understood as having networks of possibilities as their targets. This raises a further question: what are the truthmakers for the modal claims that we can derive from models? I propose that we can find truthmakers for the modal claims derived from models in actuality, even in the case of supposedly non-actual targets. I then put this framework to use by examining a case study concerning the modelling of superheavy elements.
Communication medium in theileriosis control: the factors that determine disease knowledge among smallholder farmers in Zimbabwe
Authors: Nhokwara Shelton M. , Kono Hiroichi , Kubota Satoko , Jubenkanda Mark 
Published: February 2023

AbstractTheileriosis is one of the most important tick-borne diseases that has been affecting farmers and thousands of livestock in Zimbabwe. The main government strategy to combat theileriosis is use of plunge dips with anti-tick chemicals at specified times; however, an increase in number of farmers caused a strain on government services resulting in disease outbreak. One of the key issues that have been highlighted by department of veterinary is the strain in communication and knowledge of the disease with the farmers. Hence, it is important to evaluate the communication between farmers and veterinary services and identify possible areas of strain. A field survey was conducted with 320 farmers in Mhondoro Ngezi, a district badly affected by theileriosis. Face-to-face interviews with smallholders and communal farmers were conducted between September and October 2021, and the data were analyzed using Stata 17. Communal farmers relied mainly on oral communication and had limited knowledge of theileriosis; therefore, dead cattle % was high among them. Though veterinary extension officers were the prime source of information, oral communication medium affected knowledge transferred. The results of this study recommend adoption of communication mediums that encourage retention, such as brochures and posters by veterinary extension services. The government may also partner with private players to ease pressure of increased farming population due to land reform.
The modality effect reverses in a virtual reality learning environment and influences cognitive load
Authors: Albus Patrick , Seufert Tina 
Published: February 2023

AbstractWhen Virtual Reality (VR) is used to present learning content, the three-dimensional image is often not sufficient and additional text is required, either in the form of visual or auditory text. Such additional instructional text could be particularly beneficial due to the many visual stimuli and the risk of visual working memory overload. Relieving working memory by using both channels in the audio-visual presentation, there might be more cognitive capacity available to invest in germane processes for learning. In addition, the image and the text can be processed simultaneously, supporting deeper learning processes. Based on the modality effect, it is therefore assumed that an audio-visual presentation in VR, compared to a visual-only presentation, can lead to higher learning outcomes (recall, comprehension and transfer). In a between-subjects design we analysed the modality principle in VR with 61 subjects (69% female). We hypothesized that when verbal information in VR is given auditorily instead of visually, it leads to overall higher learning outcomes. For intrinsic cognitive load we assumed no differences, but lower extraneous cognitive load and higher germane cognitive load for the audio-visual condition. However, results show a reverse modality effect. The visual-only condition showed higher learning outcome scores for recall, comprehension and transfer. As expected, the conditions showed no differences with regard to the intrinsic cognitive load. However, we also found no differences in extraneous cognitive load. Contrary to our hypothesis we found higher germane cognitive load for the visual-only condition compared to the audio-visual condition, which may be attributed to repeated reading, reading strategies or other self-regulatory strategies. Future research could focus on the use of strategies or evaluate relevant process data.
Effectiveness of invention tasks and explicit instruction in preparing intellectually gifted adolescents for learning
Authors: Lim Sue-ann , Jung Jae Yup , Kalyuga Slava 
Published: February 2023

AbstractSolving a novel problem has recently garnered some attention as a viable alternative to traditional explicit instruction in the preparation of students for learning. This study investigated the effectiveness of introducing problem-solving tasks and worked examples prior to explicit instruction, along with the use of contrast, for gifted and non-gifted adolescents. One hundred and ninety-nine students from academically selective government and Independent high schools participated in this study. The 2 × 2 × 2 research design that was used examined the effects of giftedness (i.e., gifted vs. non-gifted), instruction-type (i.e., problem-solving vs. worked examples), and structure (i.e., high vs low contrast materials) on the learning outcomes of transfer and procedural knowledge. The study also examined the impact of explicit instruction and invention-first instruction strategies on non-performance variables—self-efficacy, extraneous load, experience of knowledge gaps, and interest. The results of the study suggested that invention-first instruction may be more effective than example-first instruction in transfer, and that gifted students may benefit more from invention-first instruction than example-first instruction. The use of contrast materials was not found to affect performance. Furthermore, instruction was found to have no significant effects on the investigated non-performance variables. Collectively, these findings challenge the conventional teaching modality of explicit instruction in gifted education, and puts forward the possibility of the invention-first strategy as an effective instructional strategy for gifted students.
Using neural networks to solve linear bilevel problems with unknown lower level
Authors: Molan Ioana , Schmidt Martin 
Published: February 2023

AbstractBilevel problems are used to model the interaction between two decision makers in which the lower-level problem, the so-called follower’s problem, appears as a constraint in the upper-level problem of the so-called leader. One issue in many practical situations is that the follower’s problem is not explicitly known by the leader. For such bilevel problems with unknown lower-level model we propose the use of neural networks to learn the follower’s optimal response for given decisions of the leader based on available historical data of pairs of leader and follower decisions. Integrating the resulting neural network in a single-level reformulation of the bilevel problem leads to a challenging model with a black-box constraint. We exploit Lipschitz optimization techniques from the literature to solve this reformulation and illustrate the applicability of the proposed method with some preliminary case studies using academic and linear bilevel instances.