bluuebunny/crossref_metadata_2025 huggingface dataset:
Emission analysis in an EGR‐equipped DI diesel engine fueled by butanol‐diesel blends
Authors: Prabhu A , Harish V , Jayaprabakar J , Venkatesan K , Dhana Raju V
Published: December 2022

In this present work, the impacts of exhaust gas recirculation (EGR) on exhaust emissions of a diesel engine powered with the blending of butanol with mineral diesel under different engine loads were studied. Experimental tests were performed using butanol‐diesel blends on a single cylinder, constant speed, direct injection (DI) unmodified diesel engine at different proportions by vol%. A higher alcohol—Butanol of 10%, 20%, and 30% blended with mineral diesel fuel. Three different EGR rates of 10 to 30% were employed to reduce the oxides of nitrogen (NOx) emissions that prevailed at higher engine loads. Experimental results revealed that by increasing the EGR rates reduces nitrogen oxide emissions by up to 32% at higher loads. Whereas smoke opacity barely raised to an EGR rate of 20%. There was a rise in hydrocarbon (HC) emissions and a slight surge in carbon monoxide (CO) emissions found with butanol‐diesel blends rather than mineral diesel. NOx emissions were decreased by 29% for 70% Diesel + 30% Butanol (Bu30) blend with EGR 30% than mineral diesel fuel. There is an increase in smoke opacity with engine load because of the burning of a higher amount of energy to generate higher brake power. Smoke opacity is decreased to 68.9% using Bu30 than conventional diesel. Overall, it was found that blends of 30% of butanol and 70% of diesel can be employed in existing unmodified diesel engines.
Rational design of catalysts with earth‐abundant elements
Authors: Xu Gaomou , Cai Cheng , Zhao Wanghui , Liu Yonghua , Wang Tao
Published: December 2022

Catalysis has played a crucial role in energy sustainability, environment control, and chemical production, while the design of high‐performance catalysts is a key scientific question. In nature, biological organisms carry out catalysis with earth‐abundant metals, whereas modern industrial processes rely heavily on precious metals. This points out the necessity of designing state‐of‐the‐art catalysts with earth‐abundant elements to maintain sustainable catalysis. In this review, we will start with the fact that nature uses earth‐abundant metals to feed the planet, followed by a few successful examples of catalyst design for water oxidation. Then, we will systematically introduce the practical methods in computational catalyst design and their applications in the rational modification of EAM catalysts for various reactions. In addition, the roles of high‐throughput computations and artificial intelligence in this framework are summarized and discussed. We will also discuss the potential limitations of the framework and the strategies to overcome these challenges. Finally, we emphasize the importance of the synergistic efforts between theory and experiments in rational catalyst design with earth‐abundant elements.

This article is categorized under:

Structure and Mechanism > Reaction Mechanisms and Catalysis

Structure and Mechanism > Computational Materials Science
Designing an assay to evaluate behavioral responses to opposite‐sex conspecifics in the endangered black‐footed ferret (Mustela nigripes)
Authors: Potratz Emily J. , Brown Joel S. , Rafacz Michelle L. , Santymire Rachel M.
Published: December 2022

The endangered black‐footed ferret (ferret; Mustela nigripes) is a North American carnivore that is actively managed to reestablish self‐sustaining wild populations. Behavioral abnormalities have been reported in the breeding program and may be a limiting factor for the species' success. Our goal was to design and test an assay that examines the ferret's exploratory response to odor cues in the form of soiled bedding from opposite‐sex conspecifics. Across two breeding seasons, males and females were tested using a T‐maze that connected their home nest box to two novel nest boxes containing two different conspecific's soiled bedding. For a control, we provided two clean bedding samples. We ran linear mixed models to determine the effect of sex, type of odor cue (soiled, clean), and order of trial (first, second) on time exploring and proportion of that time spent in each behavior. Ferrets spent the majority of time in the novel nest boxes sniffing (44%), standing alert (27%) and scratching (14%). Males explored for longer than females; however, both displayed similar behaviors. Type of cue influenced behavior, with ferrets sniffing more among soiled cues than clean cues. Habituation to the assay was also observed, with less exploration and more standing alert during the second trial of the day. This study is the first step in characterizing the ferret's exploratory response and provides information regarding vital investigatory and vigilance behaviors. The continual development of this assay to further evaluate reproductive and mate choice behaviors will facilitate more successful breeding of the species.
The Use of Gendered Chatbots in Nigeria: Critical Perspectives
Authors: Borokini Favour , Wakunuma Kutoma , Akintoye Simisola
Published: December 2022

In a bid to improve service delivery and efficiency in Nigeria, the use of conversational agents such as chatbots capable of providing round the clock responses is growing. This is gaining more traction in the financial sector, particularly in fintechs where there have been significant improvements in the last year. However, not enough research has been conducted on the impact of the gendering of these conversational agents. This is concerning, especially as findings from our research reveal that the majority of chatbots currently deployed in the country are deliberately gendered to appear female, reinforcing already existing gender stereotypes within African societies. With an increase in the deployment of these bots in many other sectors, it is crucial to evaluate the significance of the gendering of these bots to ascertain the effect on gender inequality in Nigeria.
The Mohist Canon and Alternative Origins of Theoretical Science
Authors: Schemmel Matthias , Boltz William G.
Published: December 2022

Proceeding from the theoretical considerations presented in Chap. 1, the chapter provides an overall interpretation of the scientific sections of the Mohist Canon, which are presented in Chap. 3. We start with a discussion of the theoretical character of the text as it ensues from textual structures. We then discuss the ways the text reflects on different domains of pre-scientific knowledge pertaining to concepts such as spatial and corporeal extension, duration, motion, measurement, model, image and weight, thereby including what has sometimes been referred to as Mohist geometry, mechanics and optics. We compare these reflections to other historical instances of theoretical thinking, mostly from ancient Greek science and philosophy. We conclude the chapter with considerations, following from our textual analysis and intercultural comparisons, on the place of Mohist science in a long-term, global history of knowledge and what it tells us about structural necessities and historical contingencies in the rise of theoretical science.
KGEMM Behavioral Equations and Identities
Authors: Hasanov Fakhri J. , Joutz Frederick L. , Mikayilov Jeyhun I. , Javid Muhammad
Published: December 2022

This chapter reports the estimated long-run equations and identities in Sects. 7.1, 7.2, 7.3, 7.4, 7.5, 7.6, 7.7, 7.8, and 7.9 while the estimated short-run equations, i.e., final ECM specifications associated with the long-run equations are reported in Appendix B to save space in the main text. Note that the long-run and ECM equations are estimated till 2019 in the fifth version of KGEMM. Starting years of the estimations range from the 1970s to the 1990s dictated by the data availability. For the readers ease, we describe one of the long-run equations below and the rest equations here follow the same context. As an example, we select the first appeared long-run equation, i.e., Eq. (7.43).
Undoing Power Hierarchies
Authors: Ruonakoski Erika
Published: December 2022

What alternatives have been created within feminist pedagogy to question power hierarchies and to make teaching more inclusive? What approaches were adopted in the Gender and Philosophy summer schools in order to achieve these goals? After discussing these questions, I demonstrate how the concepts of “alienation”and “situation” can be used to analyse power dynamics and the framework they provide to the rest of the book.
Semantification of Mathematical LaTeX
Authors: Greiner-Petter André
Published: December 2022

In this chapter, we will focus on the research task II, i.e., we develop a new semantification process that addresses the issues of existing approaches outlined in the previous chapter. We identified two main issues with existing MathIR approaches for disambiguation and semantification of LATEX expressions. First, many semantification approaches solely focus on single tokens, such as identifiers, or the entire mathematical expression but miss to enrich the essential subexpressions between both extremes semantically.
From LaTeX to Computer Algebra System
Authors: Greiner-Petter André
Published: December 2022

This chapter addresses research tasks III and IV, i.e., implementing a system for automated semantification and translation of mathematical expressions to CAS syntax. In the previous chapter, we laid the foundation for a novel context-sensitive semantification approach that extracts the semantic information from a textual context and semantically enriches a formula with semantic LATEX macros. In this chapter, we realize this proposed semantification approach on 104 English Wikipedia articles with 6,337 mathematical expressions. However, before we continue with this main track, we first apply a novel context-agnostic machine translation approach for translations from LATEX to Mathematica.
Conclusion and FutureWork
Authors: Greiner-Petter André
Published: December 2022

This chapter summarizes and concludes the contribution of this thesis in Section 6.1 and Section 6.2, respectively. Section 6.3 provides an overview of future work projects.
Models
Authors: Bartz-Beielstein Thomas , Zaefferer Martin
Published: December 2022

This chapter presents a unique overview and a comprehensive explanation of Machine Learning (ML) and Deep Learning (DL) methods. Frequently used ML and DL methods; their hyperparameter configurations; and their features such as types, their sensitivity, and robustness, as well as heuristics for their determination, constraints, and possible interactions are presented. In particular, we cover the following methods: $$k$$
k
-Nearest Neighbor (KNN), Elastic Net (EN), Decision Tree (DT), Random Forest (RF), Extreme Gradient Boosting (XGBoost), Support Vector Machine (SVM), and DL. This chapter in itself might serve as a stand-alone handbook already. It contains years of experience in transferring theoretical knowledge into a practical guide.
Ranking and Result Aggregation
Authors: Bartz-Beielstein Thomas , Mersmann Olaf , Chandrasekaran Sowmya
Published: December 2022

This chapter explores different methods to analyze the results of Hyperparameter Tuning (HPT) experiments. Four different scenarios and two different approaches are presented. On the one hand, rankings and especially consensus rankings are introduced to aggregate the results of many different HPT results. On the other hand, statistical significance analysis and power analysis are used for a detailed analysis of single algorithms and pairwise algorithm comparisons. This chapter discusses issues with sample size determination, power calculations, hypotheses, and wrong conclusions from hypothesis testing. On top of the established methods, we add and explain severity, a frequentist approach that extends the classical concept of p-values. Mayo’s concept of severity offers one solution to these issues, and one might achieve even better results by applying severity.
Hyperparameter Tuning in German Official Statistics
Authors: Dumpert Florian , Schmidt Elena
Published: December 2022

This chapter describes the special quality requirements placed on official statistics and builds a bridge to the tuning of hyperparameters in Machine Learning (ML). To carry out the latter optimally under consideration of constraints and to assess its quality is part of the tasks of the employees entrusted with this work. The chapter sheds special light on open questions and the need for further research.
Conceptualizing Money Laundering in the 1MDB Scandal: An Analysis of Metaphors in The Sarawak Report
Authors: Lim Rachel , Yoong David
Published: December 2022

The 1Malaysia Development Berhad (1MDB) scandal is one of the most complex and widely reported scandals in the world as it involves a complicated web of financial transactions, business deals and other forms of transactions. The complexities of this scandal were first exposed by an online news portal called The Sarawak Report. Metaphors were extensively used by the primary writer, Clair Rewcastle Brown, to describe the scandal, which helps readers comprehend the magnitude of the scandal. The data used in this chapter come from 1MDB-related articles in The Sarawak Report blog. Critical metaphor analysis is used to identify, interpret, and explain the primary orientation of the conceptual metaphors found in the blog posts. This approach unpacks the metaphors used in context and reveals underlying meanings and motivations of surface level metaphors, helping readers to make connections between the subject matter and the concepts that are used to describe it. The analysis shows that the mixing of different concepts and analogies enable readers to understand the actions of the culprits, the act of money laundering, and the severity of the crime of corruption. This chapter demonstrates how metaphors can be used to make a complex and challenging issue easier to comprehend.
Top-philic dark matter in a hybrid KSVZ axion framework
Authors: Ghosh Anupam , Konar Partha , Roshan Rishav
Published: December 2022

Abstract

We explore a two-component dark matter scenario in an extended Kim-Shifman-Vainshtein-Zakharov (KSVZ) axion framework. This hybrid setup incorporates an extra SU(2)L complex singlet scalar whose lightest component plays the role of one of the dark matter, while the QCD axion of the KSVZ model acts as a second dark matter candidate. In this work, we focus on accentuating the role of vector-like quark that naturally emerges in the KSVZ extension on the dark matter and collider phenomenology. Here, we demonstrate that the presence of this colored particle can significantly affect the allowed dark matter parameter space of the scalar dark matter by opening up additional co-annihilation as well as the direct detection channels. Moreover, the interaction between the color particle with the top quark and scalar dark matter provides a unique topology to generate a boosted-top pair with considerable missing transverse momentum at the LHC. Using jet substructure variables and multivariate analysis, here we show that one can already exclude a vast region of parameter space with 139 fb−1 integrated luminosity at 14 TeV LHC.
An averaged space–time discretization of the stochastic p-Laplace system
Authors: Diening Lars , Hofmanová Martina , Wichmann Jörn
Published: December 2022

We study the stochastic p-Laplace system in a bounded domain. We propose two new space–time discretizations based on the approximation of time-averaged values. We establish linear convergence in space and 1/2 convergence in time. Additionally, we provide a sampling algorithm to construct the necessary random input in an efficient way. The theoretical error analysis is complemented by numerical experiments.
Laser interstitial thermal therapy using the Leksell Stereotactic System and a diagnostic MRI suite: how I do it
Authors: Jensdottir Margret , Sandvik Ulrika , Fagerlund Michael , Bartek Jiri
Published: December 2022

Background

Laser interstitial thermal therapy (LITT) is a stereotactic neurosurgical procedure used to treat neoplastic and epileptogenic lesions in the brain. A variety of advanced technological instruments such as frameless navigation systems, robotics, and intraoperative MRI are often described in this context, although the surgical procedure can also be performed using a standard stereotactic setup and a diagnostic MRI suite.

Methods

We report on our experience and a surgical technique using a Leksell stereotactic frame and a diagnostic MRI suite to perform LITT.

Conclusion

LITT can be safely performed using the Leksell frame and a diagnostic MRI suite, making the technique available even to neuro-oncology centers without advanced technological setup.
What drives strategic agility? Evidence from a fuzzy-set qualitative comparative analysis (FsQCA)
Authors: de Diego Ruiz Enrique , Almodóvar Paloma , del Valle Ignacio Danvila
Published: December 2022

Strategic agility is a topic that has not reached maturity and is of increasing interest for companies and academics alike. Yet few studies assess what drives strategic agility in organisations. This paper aims to review how companies are currently obtaining strategic agility and to identify the individual factors and configurations that lead to it. The study draws on a survey carried out with 40 Spanish companies in the services sector. The study then uses Qualitative Comparative Analysis (QCA) to identify the different configurations of factors that lead to strategic agility. Finally, we complement QCA analysis by performing a case study for each of the configurations that lead to strategic agility. The study reveals that there is no necessary condition to reach strategic agility and that companies reach it in five main ways, depending on different combinations of six factors: firm size, firm age, whether the firm is international, whether it competes in a turbulent environment, and whether the firm invests in i) capabilities and technologies, and ii) additional revenue models or cost-cutting mechanisms or not.
Analysis of degradation products of Novichok agents in human urine by hydrophilic interaction liquid chromatography–tandem mass spectrometry
Authors: Otsuka Mai , Yamaguchi Akinori , Miyaguchi Hajime
Published: December 2022

Purpose

The detection of hydrolysis products of Novichok agents in biological samples from victims is important for confirming exposure to these agents. However, Novichok agents are new class of nerve agent and there have been only few reports on analyses of Novichok agent degradation products. Here, we developed hydrophilic interaction liquid chromatography (HILIC)–tandem mass spectrometry (MS/MS) methods to detect Novichok agent degradation products in human urine with simple pretreatment and high sensitivity.

Methods

A Poroshell 120 HILIC-Z column was used to analyze six Novichok agent degradation products. For urine samples, we used a simple pretreatment method, which consisted of deproteinization with acetonitrile and microfiltration. We calculated the pKa values of the OH groups, the log P values, and the molecular weights to investigate the difference in chromatographic behaviors of the Novichok agent degradation products and the degradation products of conventional nerve agents.

Results

Six Novichok agent degradation products, including N-(bis-(diethylamino)methylidene)-methylphosphonamidic acid (MPGA), which could not be detected by our previous method, could be analyzed with sufficient peak shape and mutual separation. The detection limits of six Novichok agent degradation products were sufficiently low (1–50 ng/mL) and the calibration curves showed sufficient linearity. The physicochemical parameters of Novichok agent degradation products were different from those of conventional nerve agent degradation products, and this explains the difference in chromatographic behaviors.

Conclusion

Six Novichok agent degradation products were successfully analyzed by HILIC–MS/MS. Due to the absence of a derivatization step, throughput performance was higher than our previous derivatization-liquid chromatography–MS/MS method.
The impact of HER2-low status on response to neoadjuvant chemotherapy in clinically HER2-negative breast cancer
Authors: Wang Wei , Zhu Tingting , Chen Hao , Yao Yongzhong
Published: December 2022

Purpose

Low expression of HER2 (HER2-low expression) in breast cancer (BC) has unique biological characteristics. However, whether HER2-low expression has an impact on neoadjuvant chemotherapy (NACT) in HER2-negative breast cancer remains unclear.

Methods

This study reviewed the clinicopathological data of patients with BC treated with NACT at a single hospital from January 2018 to July 2022. Baseline patient characteristics, efficacy of NACT, and survival data were compared between the HER2-0 and HER2-low groups. The impact of NACT on HER2 status also was investigated. Subgroup analyses based on hormone receptor (HR) status were performed to explore the impact of HR signaling on HER2 status during chemotherapy.

Results

The progesterone receptor-positive rate in the HER2-low group was significantly higher than that in HER2-0 group. The local treatment response of the HER2-low group was worse, but the disease-free survival rate of the HER2-low group was significantly better than that of the HER2-0 group. The proportion of patients with increased HER2 immunohistochemistry score after NACT was significantly higher in the HER2-0 group. Subgroup analysis showed that the efficacy of chemotherapy in HR + patients was significantly worse than in HR− patients, and HR + patients had a higher proportion of increased HER2 immunohistochemistry score after chemotherapy. Mechanistic studies suggested that MLH1 expression loss during chemotherapy might link HR signaling and regulation of HER2 expression.

Conclusions

We found that HER2-low expressing BC exhibits differential sensitivity to chemotherapy compared to HER2-0 expressing BC. The regulation of HER2 expression by HR signaling may mediate aspects of chemoresistance.
Design and effects of the teacher-student interaction model in the online learning spaces
Authors: Xie Youru , Huang Yuling , Luo Wenjing , Bai Yucheng , Qiu Yi , Ouyang Ziru
Published: December 2022

The interaction between teachers and students is vital for promoting teaching quality. Online learning spaces have various features that can support teacher-student interaction in online learning contexts. In this study, a preliminary model was developed by analyzing the principles underlying the interaction between teachers and students and the support features of online learning spaces. Then, the interaction model was refined and validated in three rounds of teaching practice involving 31 college students. A real-time dynamic artificial intelligence analysis system was used to analyze the teacher-student interaction during three rounds of design-based research. The results showed that the model significantly fostered students’ engagement during the interaction. Moreover, students significantly improved their final exam scores and their innovative problem-solving ability after the intervention.
In Silico and In Vitro Analyses Reveal Promising Antimicrobial Peptides from Myxobacteria
Authors: Arakal Benita S. , Whitworth David E. , James Philip E. , Rowlands Richard , Madhusoodanan Neethu P. T. , Baijoo Malvika R. , Livingstone Paul G.
Published: December 2022

Antimicrobial resistance (AMR) is a global concern, and as soon as new antibiotics are introduced, resistance to those agents emerges. Therefore, there is an increased appetite for alternative antimicrobial agents to traditional antibiotics. Here, we used in silico methods to investigate potential antimicrobial peptides (AMPs) from predatory myxobacteria. Six hundred seventy-two potential AMP sequences were extracted from eight complete myxobacterial genomes. Most putative AMPs were predicted to be active against Klebsiella pneumoniae with least activity being predicted against Staphylococcus aureus. One hundred seventeen AMPs (defined here as ‘potent putative AMPs’) were predicted to have very good activity against more than two bacterial pathogens, and these were characterized further in silico. All potent putative AMPs were predicted to have anti-inflammatory and antifungal properties, but none was predicted to be active against viruses. Twenty six (22%) of them were predicted to be hemolytic to human erythrocytes, five were predicted to have anticancer properties, and 56 (47%) were predicted to be biofilm active. In vitro assays using four synthesized AMPs showed high MIC values (e.g. So_ce_56_913 250 µg/ml and Coral_AMP411 125 µg/ml against E. coli). However, antibiofilm assays showed a substantial reduction in numbers (e.g. Coral_AMP411 and Myxo_mac104 showed a 69% and 73% reduction, respectively, at the lowest concentration against E. coli) compared to traditional antibiotics. Fourteen putative AMPs had high sequence similarity to proteins which were functionally associated with proteins of known function. The myxobacterial genomes also possessed a variety of biosynthetic gene clusters (BGCs) that can encode antimicrobial secondary metabolites, but their numbers did not correlate with those of the AMPs. We suggest that AMPs from myxobacteria are a promising source of novel antimicrobial agents with a plethora of biological properties.
Ethics and non-evidence based therapies: Portuguese perspective in a global setting
Authors: Madruga Dias João
Published: December 2022

A contemporary serious lack of scientific knowledge by the general public and many decision-makers is now quite perceptible, both globally and in Portugal. Living in a science-driven technological world filled with scientific illiteracy is dangerous and a path toward disaster. Recent years brought a fairly strong global movement promoting the so-called “alternative therapy” that also affected Portugal. I propose an evidence-based ethics reflection and argumentation, both encompassing the global and the specific Portuguese reality. I debate the specific arguments used in favour of alternative therapies, demonstrating the inherent fallacies of thought, deliberate manipulation of words and concepts, and the dire consequences for global and local health politics by following this line of biased reasoning.
Chlorine Removal from Water by Biochar Derived from Various Food Waste Natural Materials
Authors: Sklivaniotis Leandros N. , Economou Polychronis , Karapanagioti Hrissi K. , Manariotis Ioannis D.
Published: December 2022

The aim of this paper was to investigate the effectiveness of pyrolyzed low-cost food waste natural materials from the food industry on the removal of chlorine from water. Biochar was produced after pyrolysis at 850 oC from malt spent rootlets (MSR), walnut shells, and apricot, olive, carob and grape kernels. The biochars were characterized for their surface area, microporosity, functional groups and pH. Continuous flow column experiments were conducted at varying flow rates to evaluate the efficiency of biochars to remove free and total chlorine. The initial free and total chlorine concentrations in water fed to the columns were 2.0 and 2.2 mg/L, respectively. The chlorine removal of free and total chlorine of all materials tested ranged from 76 to 92% and 80 to 95%, respectively, with the MSR exhibiting the highest removal. MSR biochar was subjected to the highest cumulative water volume passed through the column (162 L/g) and exhibited the highest total chlorine removal capacity (6 to 330 mg/g). Olive kernel also reached high chlorine removal (99%), while apricot kernel, grape kernel, carob seed and pulp presented poor chlorine removals.
Impact of early postoperative factors on changes in skeletal muscle mass after esophagectomy in older patients with esophageal cancer
Authors: Harada Tsuyoshi , Tatematsu Noriatsu , Ueno Junya , Koishihara Yu , Konishi Nobuko , Fukushima Takuya , Fujiwara Hisashi , Fujita Takeo , Hijikata Nanako , Wada Ayako , Ishikawa Aiko , Tsuji Tetsuya
Published: December 2022

Background

Loss of skeletal muscle mass, measured by the skeletal muscle mass index (SMI), after esophagectomy negatively impacts prognosis. However, the information to develop novel supportive care options for preventing loss of skeletal muscle mass is limited. The purpose of this retrospective cohort study was to investigate the impact of early postoperative factors on change in SMI 4 months after curative esophagectomy in older patients with esophageal cancer.

Methods

This study included 113 subjects who underwent esophagectomy between 2015 and 2020. Preoperative and postoperative SMI (cm2/m2) were calculated from computed tomography images. The percentage change in SMI 4 months after surgery (SMI%) was calculated as follows: ([postoperative SMI – preoperative SMI] ÷ preoperative SMI) × 100. Potential factors affecting percentage change of SMI after surgery were analyzed by multiple regression.

Results

The mean SMI% was – 5.6%. The percentage change (per 1%) in quadriceps muscle strength in the first month after surgery (standardized β = 0.190, p = 0.048) impacted the SMI%, which was independent of age, sex, preoperative SMI, comorbidity, pathological stage, and neoadjuvant chemotherapy.

Conclusion

Quadriceps muscle weakness in the first month after esophagectomy impacted the SMI% in a dose-dependent relationship.
Floristic composition and community analysis of woody species in Hereje Natural Forest, southwest Ethiopia
Authors: Anamo Abera , Mammo Siraj , Temesgen Mathewos
Published: December 2022

The floristic composition, diversity, and conservation status of woody plant species in Ethiopia are determined in this study. Data on vegetation are collected using a systematic random sampling method from 45 20 m × 20 m  (400m2) plots laid every 100 m along four parallel transect lines running from south to north. The Flora of Ethiopia and Eritrea identification key (Volume I–VIII) is used to identify the scientific names of all woody plant species. The Shannon–Wiener diversity index is used to calculate species diversity, whereas Sorensen's similarity coefficient is used to assess similarities and differences among plant communities. The studied forest contains 44 plant species from 29 families and 40 genera. The Fabaceae is the most dominant family, followed by the Rubiaceae and Combretaceae. In terms of habit, the collected woody species consisted of 30 (68.2%) trees and 14 (31.8%) shrubs. The two most frequent species are Syzygium guineense (51.11%) and Maytenus gracilipes (46.66%). Three plant community types are identified using Agglomerative Hierarchical Cluster Analysis. Most species (Calpurnia aurea-Combretum molle) are observed in community type two. The study is generally limited to the floristic and diversity of woody plant species. Therefore, a thorough investigation of all species' floristic composition, population structure, regeneration status, and ecological aspects is recommended.
Health Disparities Experienced by Hispanic Americans with Multiple Myeloma: A Systematic Review
Authors: Anampa-Guzmán Andrea , Alam Sara Taveras , Abuali Inas , Al Hadidi Samer
Published: December 2022

Health disparities in multiple myeloma (MM) disproportionately affect minorities. Characterization of health disparities encountered by Hispanic Americans with MM is necessary to identify gaps and inform future strategies to eliminate them. We performed a systematic review of publications that described health disparities relevant to Hispanic Americans with MM through December 2021. We included all original studies which compared incidence, treatment, and/or outcomes of Hispanic Americans with other ethnic groups. Eight hundred and sixty-eight articles were identified of which 22 original study articles were included in our systematic review. The number of publications varied over time with the highest number of studies (32%) published in 2021. Most of the published studies (59%) reported worse outcomes for Hispanic Americans with MM compared to other ethnic groups. There is growing evidence that Hispanic Americans with MM are facing a multitude of disparities that require immediate attention and solutions.
A Multi‐Hazard Risk Framework to Stress‐Test Water Supply Systems to Climate‐Related Disruptions
Authors: Becher Olivia , Pant Raghav , Verschuur Jasper , Mandal Arpita , Paltan Homero , Lawless Mark , Raven Emma , Hall Jim
Published: December 2022

Water utilities' supply systems are vulnerable to several climate‐related hazards, including droughts, floods and cyclones. Here we propose a generally applicable framework for conducting multi‐hazard risk assessments of water supply systems and use it to quantify the impact of present and future climate extremes on the national water supply network in Jamaica. The proposed framework involves stress‐testing a model of the system with a large set of spatially coherent drought, cyclone and pluvial and fluvial flood events to calculate the number of water users whose supplies would be disrupted during an event, that is, the Customer disruption days (CDD). We estimate the total multi‐hazard annual expected disruption to be approximately 5 days per year per utility customer under present conditions. This is increased by a factor of between 2 and 2.5 when end‐of‐century climate scenarios are propagated through the model. Our analysis shows that more high probability drought events lead to greater CDD compared with asset damage events. However, extreme asset damage events, despite manifesting over shorter timescales (days) compared to drought events (months), can lead to more widespread CDD. This quantified risk framework would allow utility managers to compare the risk of both asset damage‐ and water shortage‐induced disruptions via a common, decision‐relevant metric. However, applications to other utilities would require tailored hazard modeling approaches. The proposed risk assessment is intended to inform prioritization of infrastructure investments, ranging from asset protection to drought mitigation projects, with the goal of enhancing water supply resilience in the face of a changing climate.
Projected Impact of Increased Global Warming on Heat Stress and Exposed Population Over Africa
Authors: Fotso‐Nguemo Thierry C. , Weber Torsten , Diedhiou Arona , Chouto Steven , Vondou Derbetini A. , Rechid Diana , Jacob Daniela
Published: December 2022

This study investigates the impact of increased global warming on heat stress changes and the potential number of people exposed to heat risks over Africa. For this purpose a heat index has been computed based on an ensemble‐mean of high‐resolution regional climate model simulations from the Coordinated Output for Regional Evaluations embedded in the COordinated Regional Climate Downscaling EXperiment, under two Representative Concentration Pathways (RCPs) scenarios (RCP2.6 and RCP8.5), combined with projections of population growth developed based on the Shared Socioeconomic Pathways (SSPs) scenarios (SSP1 and SSP5). Results show that by the late 21st century, the increased global warming is expected to induce a 12‐fold increase in the area extent affected by heat stress of high‐risk level. This would result in an increase of about 10%–30% in the number of days with high‐risk heat conditions, as well as about 6%–20% in their magnitude throughout the seasonal cycle over West, Central, and North‐East Africa. Therefore, and because of the lack of adaptation and mitigation policies, the exacerbation of ambient heat conditions could contribute to the exposure of about 2–8.5 million person‐events to heat stress of high‐risk level over Burkina Faso, Ghana, Niger, and Nigeria. Furthermore, it was found that the interaction effect between the climate change and population growth seems to be the most dominant in explaining the total changes in exposure due to moderate and high heat‐related risks over all subregions of the African continent.
Immune cell populations differ in patients undergoing revision total knee arthroplasty for arthrofibrosis
Authors: Limberg Afton K. , Salib Christopher G. , Tibbo Meagan E. , Vargas-Hernandez Juan S. , Bettencourt Jacob W. , Bayram Banu , Berry Charlotte E. , Dudakovic Amel , Bolon Brad , van Wijnen Andre J. , Morrey Mark E. , Sanchez-Sotelo Joaquin , Berry Daniel J. , Carter Jodi M. , Abdel Matthew P.
Published: December 2022

Arthrofibrosis following total knee arthroplasty (TKA) is a debilitating condition typically diagnosed based on clinical findings. To gain insight into the histopathologic immune cell microenvironment of arthrofibrosis, we assessed the extent of tissue fibrosis and quantified immune cell populations in specific tissue regions of the posterior capsule. We investigated specimens from three prospectively-collected, matched cohorts, grouped as patients receiving a primary TKA for osteoarthritis, revision TKA for arthrofibrosis, and revision TKA for non-arthrofibrotic, non-infectious reasons. Specimens were evaluated using hematoxylin and eosin staining, picrosirius red staining, immunofluorescence, and immunohistochemistry with Aperio®-based digital image analysis. Increased collagen deposition and increased number of α-SMA/ACTA2 expressing myofibroblasts were present in the arthrofibrosis group compared to the two non-arthrofibrotic groups. CD163 + macrophages were the most abundant immune cell type in any capsular sample with specific enrichment in the synovial tissue. CD163 + macrophages were significantly decreased in the fibrotic tissue region of arthrofibrosis patients compared to the patients with primary TKA, and significantly increased in adipose tissue region of arthrofibrotic specimens compared to non-arthrofibrotic specimens. Synovial CD117 + mast cells were significantly decreased in arthrofibrotic adipose tissue. Together, these findings inform diagnostic and targeted therapeutic strategies by providing insight into the underlying pathogenetic mechanisms of arthrofibrosis.
Higher-order interactions shape microbial interactions as microbial community complexity increases
Authors: Morin Manon A. , Morrison Anneliese J. , Harms Michael J. , Dutton Rachel J.
Published: December 2022

Non-pairwise interactions, or higher-order interactions (HOIs), in microbial communities have been described as significant drivers of emergent features in microbiomes. Yet, the re-organization of microbial interactions between pairwise cultures and larger communities remains largely unexplored from a molecular perspective but is central to our understanding and further manipulation of microbial communities. Here, we used a bottom-up approach to investigate microbial interaction mechanisms from pairwise cultures up to 4-species communities from a simple microbiome (Hafnia alvei,Geotrichum candidum,Pencillium camembertiandEscherichia coli). Specifically, we characterized the interaction landscape for each species combination involvingE. coliby identifyingE. coli’sinteraction-associated mutants using an RB-TnSeq-based interaction assay. We observed a deep reorganization of the interaction-associated mutants, with very few 2-species interactions conserved all the way up to a 4-species community and the emergence of multiple HOIs. We further used a quantitative genetics strategy to decipher how 2-species interactions were quantitatively conserved in higher community compositions. Epistasis-based analysis revealed that, of the interactions that are conserved at all levels of complexity, 82% follow an additive pattern. Altogether, we demonstrate the complex architecture of microbial interactions even within a simple microbiome, and provide a mechanistic and molecular explanation of HOIs.
The ground beetle Pseudoophonus rufipes gut microbiome is influenced by the farm management system
Authors: Magagnoli Serena , Alberoni Daniele , Baffoni Loredana , Martini Antonio , Marini Francesca , Di Gioia Diana , Mazzon Martina , Marzadori Claudio , Campanelli Gabriele , Burgio Giovanni
Published: December 2022

Intensive conventional farm management, characterized by high agrochemicals input, could alter the composition of microbial communities with potential negative effects on both functional traits and the ecosystem services provided. In this study, we investigated the gut microbial composition of a high ecological relevance carabid Pseudoophonus rufipes, sampled in two fields subjected to conventional and organic management practices. Carabids’ gut microbiota was analyzed via qPCR and NGS. Profound differences between the microbial composition of organic and conventional samples were detected: the abundance of Tenericutes and Proteobacteria was significant higher in organic and conventional samples, respectively. Spiroplasmataceae and Bifidobacteriaceae families were significantly more abundant in samples from organic management, while Enterococcaceae, Morganellaceae and Yersiniaceae were more abundant in samples from conventional management. The diverse gut microbial composition of insects between the two management systems is related to the pressure of environmental stressors and it may representing an important bioindication of ecological functions and services provided by a carabid species.
An ancestral hard-shelled sea turtle with a mosaic of soft skin and scutes
Authors: De La Garza Randolph Glenn , Madsen Henrik , Sjövall Peter , Osbӕck Frank , Zheng Wenxia , Jarenmark Martin , Schweitzer Mary H. , Engdahl Anders , Uvdal Per , Eriksson Mats E. , Lindgren Johan
Published: December 2022

The transition from terrestrial to marine environments by secondarily aquatic tetrapods necessitates a suite of adaptive changes associated with life in the sea, e.g., the scaleless skin in adult individuals of the extant leatherback turtle. A partial, yet exceptionally preserved hard-shelled (Pan-Cheloniidae) sea turtle with extensive soft-tissue remains, including epidermal scutes and a virtually complete flipper outline, was recently recovered from the Eocene Fur Formation of Denmark. Examination of the fossilized limb tissue revealed an originally soft, wrinkly skin devoid of scales, together with organic residues that contain remnant eumelanin pigment and inferred epidermal transformation products. Notably, this stem cheloniid—unlike its scaly living descendants—combined scaleless limbs with a bony carapace covered in scutes. Our findings show that the adaptive transition to neritic waters by the ancestral pan-chelonioids was more complex than hitherto appreciated, and included at least one evolutionary lineage with a mosaic of integumental features not seen in any living turtle.
Comparison of changes in lipid profiles of premenopausal women with early-stage breast cancer treated with different endocrine therapies
Authors: Wang Kaiyue , Shen Lu , Tian Wei , Zhang Suzhan
Published: December 2022

Adjuvant endocrine therapy improves the prognosis of early breast cancer with hormone receptor positivity. However, there is no systematic report on the effect of endocrine therapy (particularly ovarian function suppression, OFS) on serum lipids in premenopausal women. This retrospective cohort study aimed to determine whether various endocrine treatments had different effects on blood lipids. This study enrolled 160 premenopausal patients with stage I–III breast cancer in eastern China. The initial diagnostic information was retrieved from patient's medical records, including age at the time of diagnosis, tumor characteristics, anticancer treatment and past medical history. The changes in blood lipids in patients receiving different types of endocrine therapy were compared at the 3rd, 6th, 12th, and 24th months after initiating endocrine therapy. Generalized linear mixed model was used in our analyses. Our data revealed that low-density lipoprotein cholesterol (LDL-C) levels in patients with tamoxifen (TAM) were significantly lower in the 6th, 12th, and 24th months than that in the 3rd month, while high-density lipoprotein cholesterol (HDL-C) levels in the 6th, 12th, and 24th months were significantly higher than that in the 3rd month, indicating that blood lipid levels generally improved with time. While in TAM plus OFS group, HDL-C levels were significantly higher in the 24th month than in the 3rd month, total cholesterol (TC) levels were significantly higher in the 24th month than in the 6th month. The lipid profiles of OFS plus aromatase inhibitor (AI) group did not show significant differences at any time point but were significantly higher than those of the other two groups especially in LDL and TC. TAM group tended to have lower serum lipid levels. With longer follow-up, no statistically significant difference in values was observed between TAM and TAM plus OFS groups at various time points. Compared with the other two groups, OFS plus AI group presented an increasing trend toward LDL-C and TC. The risk of dyslipidemia requires further investigation using a large sample size.
Prediction and risk assessment of sepsis-associated encephalopathy in ICU based on interpretable machine learning
Authors: Lu Xiao , Kang Hongyu , Zhou Dawei , Li Qin
Published: December 2022

Sepsis-associated encephalopathy (SAE) is a major complication of sepsis and is associated with high mortality and poor long-term prognosis. The purpose of this study is to develop interpretable machine learning models to predict the occurrence of SAE after ICU admission and implement the individual prediction and analysis. Patients with sepsis admitted to ICU were included. SAE was diagnosed as glasgow coma score (GCS) less than 15. Statistical analysis at baseline was performed between SAE and non-SAE. Six machine learning classifiers were employed to predict the occurrence of SAE, and the adjustment of model super parameters was performed by using Bayesian optimization method. Finally, the optimal algorithm was selected according to the prediction efficiency. In addition, professional physicians were invited to evaluate our model prediction results for further quantitative assessment of the model interpretability. The preliminary analysis of variance showed significant differences in the incidence of SAE among patients with pathogen infection. There were significant differences in physical indicators like respiratory rate, temperature, SpO2 and mean arterial pressure (P < 0.001). In addition, the laboratory results were also significantly different. The optimal classification model (XGBoost) indicated that the best risk factors (cut-off points) were creatinine (1.1 mg/dl), mean respiratory rate (18), pH (7.38), age (72), chlorine (101 mmol/L), sodium (138.5 k/ul), SAPSII score (23), platelet count (160), and phosphorus (2.4 and 5.0 mg/dL). The ranked features derived from the best model (AUC is 0.8837) were mechanical ventilation, duration of mechanical ventilation, phosphorus, SOFA score, and vasopressin usage. The SAE risk prediction model based on XGBoost created here can make very accurate predictions using simple indicators and support the visual explanation. The interpretable model was effectively evaluated by professional physicians and can help them predict the occurrence of SAE more intuitively.