bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimizing Peer Distribution of Syphilis Self-Testing Among Men Who Have Sex with Men in China: A Multi-City Pragmatic Randomized Controlled Trial
Authors: Wang Yajie , Zhang Wei , Gong Xiao , Ong Jason J. , Marks Michael , Zhao Peizhen , Tucker Joseph D. , Tang Weiming , Wu Dan , Wang Cheng 
Published: January 2023

AbstractSyphilis testing uptake is low among men who have sex with men (MSM) around the world. Syphilis self-testing (SST) may complement facility-based testing; the distribution model is yet to be explored. This study aimed to investigate the effectiveness of peer distribution of syphilis self-testing on promoting syphilis testing. We conducted a three-arm, unblinded, parallel individually randomized controlled trial among MSM in three cities in Guangdong, China. Inclusion criteria were: men who were born biologically male, aged 18 or above, have ever had sex with a man, will refer the interventions to peers, and will take the three-month follow-up survey. Enrolled indexes were randomly assigned in a 1:1:1 ratio into standard-of-care arm (SOC arm), standard SST delivery arm (S-SST arm), and a web-based referral link SST delivery arm (RL-SST arm). The primary outcome was the number of returned photograph-verified syphilis testing results per index. A total number of 300 indexes were enrolled, with 100 indexes in each arm. The number of verified syphilis tests per index conducted by alters was 0.05 in the control arm, 0.51 in the S-SST arm, and 0.31 in the RL-SST arm. The cost per alter tested was $760.60 for SOC, $83.78 for S-SST, and $93.10 for RL-SST. Minimal adverse event was reported among both indexes and alters during the study. This study showed that peer distribution of SST could improve syphilis testing uptake among MSM in China compared to facility-based testing. This approach warrants further consideration as part of expanding syphilis self-testing.
Model-agnostic feature importance and effects with dependent features: a conditional subgroup approach
Authors: Molnar Christoph , König Gunnar , Bischl Bernd , Casalicchio Giuseppe 
Published: January 2023

AbstractThe interpretation of feature importance in machine learning models is challenging when features are dependent. Permutation feature importance (PFI) ignores such dependencies, which can cause misleading interpretations due to extrapolation. A possible remedy is more advanced conditional PFI approaches that enable the assessment of feature importance conditional on all other features. Due to this shift in perspective and in order to enable correct interpretations, it is beneficial if the conditioning is transparent and comprehensible. In this paper, we propose a new sampling mechanism for the conditional distribution based on permutations in conditional subgroups. As these subgroups are constructed using tree-based methods such as transformation trees, the conditioning becomes inherently interpretable. This not only provides a simple and effective estimator of conditional PFI, but also local PFI estimates within the subgroups. In addition, we apply the conditional subgroups approach to partial dependence plots, a popular method for describing feature effects that can also suffer from extrapolation when features are dependent and interactions are present in the model. In simulations and a real-world application, we demonstrate the advantages of the conditional subgroup approach over existing methods: It allows to compute conditional PFI that is more true to the data than existing proposals and enables a fine-grained interpretation of feature effects and importance within the conditional subgroups.
Undergraduate students’ beliefs about diverse approaches to making engineering design decisions: Exploring change during a capstone course
Authors: Leonard Alexia , Guanes Giselle , Dringenberg Emily 
Published: January 2023

AbstractWell-structured, de-contextualized problems that can be solved using solely technical approaches remain a large component of the engineering education curriculum. As a result, students may mistakenly believe that all engineering work can be done the same way—without the use of other approaches. Capstone design courses are an established way of exposing undergraduate students to ill-structured design tasks that more realistically reflect engineering practice. Yet, little is known about the influence of their capstone design experiences on their beliefs about how engineering design decisions are made. Our study compared students’ beliefs about four diverse approaches (technical, empathic, guess-based, and experience-based) to making engineering design decisions at the start of their capstone to their beliefs held at the end of their capstone. We conducted and analyzed qualitative transcripts from one-on-one, semi-structured interviews with 17 capstone students. We found little evidence that students’ experience in capstone courses changed their beliefs about diverse approaches to making engineering design decisions. The minimal change that we did find in students’ beliefs was primarily about guess-based approaches, and that change was not uniform amongst the students who did demonstrate change. Our findings point to the resiliency of students’ beliefs about approaches to design decisions throughout an engineering capstone design experience. Therefore, we recommend instructors foster reflexivity within their classrooms to disrupt these limited, normative beliefs about the approaches needed to make engineering design decisions.
Societal Attitudes Towards Autism (SATA): Validation of the Greek Version in the General Population
Authors: Zarokanellou Vasiliki , Gryparis Alexandros , Papatheodorou Paraskevi , Tatsis Giorgos , Tafiadis Dionysios , Papadopoulos Angelos , Voniati Louiza , Siafaka Vassiliki 
Published: January 2023

AbstractThis study examined the validity of the Greek version of the Societal Attitudes Towards Autism (SATA) scale in a Greek community sample (n = 633) and explored how the demographic variables of the sample modulate knowledge and attitudes regarding people with Autism Spectrum Disorder (ASD). The principal component analysis confirmed the three-dimension model and explained 40.5% of the variance. All Cronbach’s alpha values obtained were over 0.70. SATA’s subscales were significantly and positively correlated, indicating good internal reliability. Participants presented moderate knowledge about ASD and mediocre positive attitudes towards people with ASD. Gender, age, and educational level significantly affected SATA total scores. Overall, this Greek version of SATA showed acceptable psychometric properties, indicating that can be a reliable scale for use.
Functionalized Polyethylene Glycol as a Catalyst for Esterification of Salicylic Acid
Authors: Farouq Rania , Selim Yehia 
Published: January 2023

AbstractIn this work, two catalysts based on polyethylene glycol (PEG) containing sulfonic acid group and the −COOH group of citric acid (CA) were synthesized. Characterization of the −SO3H functionalized PEG and citric acid functionalized PEG has been carried out using FT–IR. The acidity of PEG–SO3H and PEG–CA has been explored to investigate their catalytic efficiency towards eco-friendly production of methyl salicylate via esterification of salicylic acid using methanol as a reactant as well as solvent. Methanol to acid molar ratios of 4:1, 6:1, 8:1, and 10:1 was applied. The sulfonated PEG is found to be a very active solid acid catalyst giving high yields (82%) under the optimized reaction conditions (10:1 M ratio of methanol to acid; reaction temperature, 65 °C; reaction time, 150 min with catalyst loading of 1.5%. In comparison with the catalytic activity of H2SO4,PEG–SO3H, and PEG-CA; the PEG–SO3H surpassed the catalytic activity of both H2SO4and PEG–CA. The IEC of PEG–SO3H was 4 meq/g. And the maximum water uptake of PEG-SO3H was 8.25%.
Human-induced earthquakes: E-PIE—a generic tool for Evaluating Proposals of Induced Earthquakes
Authors: Foulger G. R. , Wilkinson M. W. , Wilson M. P. , Mhana N. , Tezel T. , Gluyas J. G. 
Published: January 2023

AbstractThe HiQuake database documents all cases of earthquake sequences proposed on scientific grounds to have been induced by anthropogenic industrial activity. Because these cases range from being highly plausible to unpersuasive, stakeholders have requested cases to be allocated plausibility grades. Since no questionnaire scheme existed that was sufficiently generalized to be applied to the diverse cases in HiQuake, we developed a new scheme for the task. Our scheme for Evaluating Proposals of Induced Earthquakes (E-PIE) comprises nine generalized questions with a simple weighting system to adjust for the variable diagnostic strength of different observations. Results are illustrated using a simple colored pie chart. We describe the E-PIE scheme and illustrate its application in detail using the example cases of the Groningen gas field in the Netherlands, the November 2017 M5.4 Pohang Enhanced Geothermal Systems-related earthquake sequence in South Korea, and the 2001 deep-penetrating bombing of Tora Bora, Afghanistan. To test the performance of E-PIE, five analysts independently applied it to a suite of 23 diverse cases from HiQuake. By far the most diagnostic questions are those concerning spatial and temporal correlations with industrial effects. Other data are diagnostically subsidiary. For individual cases, the agreement between analysts correlated positively with the strength of evidence for human induction. E-PIE results agree well with those from a specialist scheme tailored to fluid-injection cases. Its strong performance confirms its suitability to apply to the entire HiQuake database.
China’s Monetary Policy and the Loan Market: How Strong is the Credit Channel in China?
Authors: Breitenlechner Max , Nuutilainen Riikka 
Published: January 2023

AbstractWe study the macroeconomic relevance of credit supply effects in the transmission of Chinese monetary policy. Using combinations of zero and sign restrictions in a structural vector autoregressive framework, we simultaneously identify monetary policy shocks and supply dynamics in the loan market. Our results show that policy shocks which coincide with loan supply effects account for roughly 60% of the overall effects of policy induced output dynamics. Moreover, we find that it takes roughly one year that banks adjust their lending strategies and loan supply effects unfold completely. Overall, our results provide robust empirical evidence that the credit channel constitutes an important and economically relevant transmission channel for monetary policy in China.
Assessment of hepatic fat content and prediction of myocardial fibrosis in athletes by using proton density fat fraction sequence
Authors: Liu Tao , Dong Ping , Zhou Jin-Rong , Chen Jing , Luo Qian-Feng , Long Shuang , Li Jia-Li , Chen Dong , Li Yuan-Sheng 
Published: January 2023

Abstract
Purpose
To explore the characteristics of the hepatic fat content in athletes, and predict late gadolinium enhancement (LGE) based on magnetic resonance imaging-proton density fat fraction (MRI-PDFF).

Material and methods
From March 2020 to March 2021, 233 amateur athletes and 42 healthy sedentary controls were prospectively recruited. The liver fat content of four regions of interest (ROIs 1–4), the mean liver fat fraction (FF), cardiac function, and myocardium LGE were recorded, respectively. The values of ROIs 1–4 and FF were compared between athletes and controls. According to the liver fat content threshold for distinguishing athletes and controls, the cutoff total exercise time that induced a change in liver fat was obtained. The correlations among the liver fat content, cardiac function, and other parameters were analyzed. Moreover, the liver fat content was used to predict myocardium LGE by logistic regression.

Results
There were significant differences for the values of ROI 1, ROI 3, ROI 4, and FF between athletes and controls (allp< 0.05). The cutoff total exercise time for inducing a change in the liver fat content was 1680 h (area under the curve [AUC] = 0.593, specificity = 83.3,p< 0.05). Blood indexes, cardiac function, and basic clinical parameters were related to liver fat content (allp< 0.05). The prediction model for LGE had an AUC value of 0.829 for the receiver operator characteristic curve.

Conclusion
MRI-PDFF could assess liver fat content and predict cardiac fibrosis in athletes for risk stratification and follow-up.
Leaf thermal tolerance and sensitivity of temperate tree species are correlated with leaf physiological and functional drought resistance traits
Authors: Münchinger Ines Katharina , Hajek Peter , Akdogan Berivan , Caicoya Astor Toraño , Kunert Norbert 
Published: January 2023

AbstractClimate change is causing more frequent and severe climatic events, such as extreme heat and co-occurring drought, potentially accelerating tree mortality. Which tree species will cope better with those extreme events is still being researched. This study focuses on heat as a physiological stress factor and interspecific variation of thermal tolerance and sensitivity traits in 15 temperate coniferous and broad-leaved tree species. We investigate (1) whether thermal tolerance and sensitivity traits correlate with a drought-related physiological trait, particularly the leaf turgor loss point (πtlp, wilting point), and (2) how thermal tolerance and sensitivity traits co-vary within different tree-functional types classified by morphological and physiological traits of the leaf, i.e., leaf mass per area (LMA) and percentage loss of area (PLA). The study was carried out in the Traunstein Forest Dynamics Plot of the ForestGEO network in Germany. The temperature response of the maximum quantum yield of photosystem II (Fv/Fm) on leaf discs was determined, from which various physiological leaf traits were estimated, one of which is the breaking point temperature (T5), the temperature at which Fv/Fm declines by 5%. Additionally, the temperature of 50% (T50) and 95% (T95) decline in Fv/Fm was evaluated. The decline width between T50 and T5 (DWT50−T5) was taken as an indicator of the species’ thermal sensitivity. The breaking point temperature ranged from 35.4 ± 3.0 to 47.9 ± 3.9 °C among the investigated tree species and T50 ranged between 46.1 ± 0.4 and 53.6 ± 0.7 °C. A large interspecific variation of thermal tolerance and sensitivity was found. European ash (Fraxinus excelsior L.) was the most heat-sensitive species, while Wild cherry (Prunus avium L.) was the least heat-sensitive species. Species with a more negative πtlp tended to have a higher breaking point temperature than species with a less negative πtlp. A lower thermal sensitivity characterized species with a higher LMA, and high PLA was found in species with low thermal sensitivity. Accordingly, species with thicker and tougher leaves have lower thermal sensitivity which coincides with a lower wilting point. We conclude that species that develop drought-adapted foliage can cope better with heat stress. Further, they might be able to maintain transpirational cooling during combined heat and drought stress, which could lessen their mortality risk during climatic extremes.
A survey on observability of Boolean control networks
Authors: Zhang Kuize 
Published: January 2023

AbstractObservability is a fundamental property of a partially observed dynamical system, which means whether one can use an input sequence and the corresponding output sequence to determine the initial state. Observability provides bases for many related problems, such as state estimation, identification, disturbance decoupling, controller synthesis, etc. Until now, fundamental improvement has been obtained in observability of Boolean control networks (BCNs) mainly based on two methods—Edward F. Moore’s partition and our observability graph (or their equivalent representations found later based on the semitensor product (STP) of matrices (where the STP was proposed by Daizhan Cheng)), including necessary and sufficient conditions for different types of observability, extensions to probabilistic Boolean networks (PBNs) and singular BCNs, even to nondeterministic finite-transition systems (NFTSs); and the development (with the help of the STP of matrices) in related topics, such as computation of smallest invariant dual subspaces of BNs containing a set of Boolean functions, multiple-experiment observability verification/decomposition in BCNs, disturbance decoupling in BCNs, etc. This paper provides a thorough survey for these topics. The contents of the paper are guided by the above two methods. First, we show that Moore’s partition-based method closely relates the following problems: computation of smallest invariant dual subspaces of BNs, multiple-experiment observability verification/decomposition in BCNs, and disturbance decoupling in BCNs. However, this method does not apply to other types of observability or nondeterministic systems. Second, we show that based on our observability graph, four different types of observability have been verified in BCNs, verification results have also been extended to PBNs, singular BCNs, and NFTSs. In addition, Moore’s partition also shows similarities between BCNs and linear time-invariant (LTI) control systems, e.g., smallest invariant dual subspaces of BNs containing a set of Boolean functions in BCNs vs unobservable subspaces of LTI control systems, the forms of quotient systems based on observability decomposition in both types of systems. However, there are essential differences between the two types of systems, e.g., “all plausible definitions of observability in LTI control systems turn out to be equivalent” (by Walter M. Wonham 1985), but there exist nonequivalent definitions of observability in BCNs; the quotient system based on observability decomposition always exists in an LTI control system, while a quotient system based on multiple-experiment observability decomposition does not always exist in a BCN.
Organizational and psychological measures for data center energy efficiency: barriers and mitigation strategies
Authors: Hanus Nichole , Newkirk Alex , Stratton Hannah 
Published: January 2023

AbstractIt was last estimated that in 2020, data centers comprised approximately 2% of total US electricity consumption, with an estimated annual growth rate of 4%. As our country increasingly relies on information technology (IT), our data centers (DCs) will need to increase their energy efficiency (EE) to stabilize their energy consumption. The task of studying EE in DCs is complicated by the interconnected nature of humans and mission-critical technical systems. Moreover, the literature tends to focus on technology solutions such as improvements to IT equipment, cooling infrastructure, and software, without addressing organizational and psychological drivers. Our research demystifies the complex interactions between humans and DCs, by asking What non-technical barriers impede EE investment decision-making and/or implementing energy management strategies? To begin to answer this question, we perform a literature review of 86 resources, ranging from peer-reviewed journal publications to handbooks. We also consider related fields such as organizational behavioral management and energy intensive buildings. We develop a public Zotero library, perform content coding, and complete a rudimentary network analysis. Our findings from the literature review suggest that (1) technological solutions are abundant in the literature but fall short of providing practical guidance on the pitfalls of implementation, (2) making energy efficiency a priority at the executive level of organizations will be largely ineffective if the IT and facilities staff are not directly incentivized to increase EE, and (3) there is minimal current understanding of how the individual psychologies of IT and facilities staff affect EE implementation in DCs. In the next phase of our research, we plan to interview data center operators/experts to ground-truth our literature findings and collaboratively design decarbonization policy solutions that target organizational structure, empower individual staff, and foster a supportive external market.
Analysis of Preventive Measures Against DDoS Attacks in Smart Grid
Authors: Gururaj H. L. , Swathi B. H. , Trupti R. , Darshan Urs R. , Rajendra A. B. , Paramesha K. 
Published: January 2023

AbstractIn recent times, the number of cyberattacks has escalated quickly and predominantly. There is no particular victim of this attack as it has outrageously tampered with all the domains in society. Cogitating this issue, the paper focuses on the cyberattacks on smart grids and endeavors some prevention techniques for the DDOS attacks. The researchers are amidst a paradigm shift, and the factors affecting this must be addressed and dealt with. It talks about a radical transformation of the medieval grids to smart grids and the technologies used and some of the possible solutions.
“Hey SyRI, tell me about algorithmic accountability”: Lessons from a landmark case
Authors: Wieringa Maranke 
Published: January 2023

Abstract
The promised merits of data-driven innovation in general and algorithmic systems in particular hardly need enumeration. However, as decision-making tasks are increasingly delegated to algorithmic systems, this raises questions about accountability. These pressing questions of algorithmic accountability, particularly with regard to data-driven innovation in the public sector, deserve ample scholarly attention. Therefore, this paper brings together perspectives from governance studies and critical algorithm studies to assess how algorithmic accountability succeeds or falls short in practice and analyses the Dutch System Risk Indication (SyRI) as an empirical case. Dissecting a concrete case teases out to which degree archetypical accountability practices and processes function in relation to algorithmic decision-making processes, and which new questions concerning algorithmic accountability emerge therein. The case is approached through the analysis of “scavenged” material. It was found that while these archetypical accountability processes and practices can be incredibly productive in dealing with algorithmic systems they are simultaneously at risk. The current accountability configurations hinge predominantly on the ex ante sensitivity and responsiveness of the political fora. When these prove insufficient, mitigation in medias res/ex post is very difficult for other actants. In part, this is not a new phenomenon, but it is amplified in relation to algorithmic systems. Different fora ask different kinds of medium-specific questions to the actor, from different perspectives with varying power relations. These algorithm-specific considerations relate to the decision-making around an algorithmic system, their functionality, and their deployment. Strengthening ex ante political accountability fora to these algorithm-specific considerations could help mitigate this.
Analyzing Social Media Messaging on Masks and Vaccines: A Case Study on Misinformation During the COVID-19 Pandemic
Authors: Trotochaud Marc , Smith Elizabeth , Hosangadi Divya , Sell Tara Kirk 
Published: January 2023

Abstract
Misinformation and disinformation during infectious disease outbreaks can hinder public health responses. This analysis examines comments about masks and COVID-19 vaccines on Twitter during the first six months of the COVID-19 pandemic. We conducted a content analysis of 6,600 randomly selected English-language tweets, examining tweets for health, political, of societal frames; inclusion of true information, false information, partially true/misleading information, and/or opinion; political components; risk frames; and use of specific types of rumor. We found false and partially false information in 22% of tweets in which we were able to assess veracity. Tweets with misinformation were more likely to mention vaccines, be political in nature, and promote risk elevating messages (p<0.5). We also found false information about vaccines as early as January 2020, nearly a year before COVID-19 vaccines became widely available. These findings highlight a need for new policies and strategies aimed to counter harmful and misleading messaging.