bluuebunny/crossref_metadata_2025 huggingface dataset:
Process optimization for gold nanoparticles biosynthesis by Streptomyces albogriseolus using artificial neural network, characterization and antitumor activities
Authors: El-Naggar Noura El-Ahmady , El-Sawah Asmaa A. , Elmansy Mohamed F. , Elmessiry Omar T. , El-Saidy Mohanad E. , El-Sherbeny Mostafa K. , Sarhan Mohamed T. , Elhefnawy Aya Amin , Dalal Shimaa R.
Published: February 2024

Gold nanoparticles (GNPs) are highly promising in cancer therapy, wound healing, drug delivery, biosensing, and biomedical imaging. Furthermore, GNPs have anti-inflammatory, anti-angiogenic, antioxidants, anti-proliferative and anti-diabetic effects. The present study presents an eco-friendly approach for GNPs biosynthesis using the cell-free supernatant of Streptomyces albogriseolus as a reducing and stabilizing agent. The biosynthesized GNPs have a maximum absorption peak at 540 nm. The TEM images showed that GNPs ranged in size from 5.42 to 13.34 nm and had a spherical shape. GNPs have a negatively charged surface with a Zeta potential of − 24.8 mV. FTIR analysis identified several functional groups including C–H, –OH, C–N, amines and amide groups. The crystalline structure of GNPs was verified by X-ray diffraction and the well-defined and distinct diffraction rings observed by the selected area electron diffraction analysis. To optimize the biosynthesis of GNPs using the cell-free supernatant of S. albogriseolus, 30 experimental runs were conducted using central composite design (CCD). The artificial neural network (ANN) was employed to analyze, validate, and predict GNPs biosynthesis compared to CCD. The maximum experimental yield of GNPs (778.74 μg/mL) was obtained with a cell-free supernatant concentration of 70%, a HAuCl4 concentration of 800 μg/mL, an initial pH of 7, and a 96-h incubation time. The theoretically predicted yields of GNPs by CCD and ANN were 809.89 and 777.32 μg/mL, respectively, which indicates that ANN has stronger prediction potential compared to the CCD. The anticancer activity of GNPs was compared to that of doxorubicin (Dox) in vitro against the HeP-G2 human cancer cell line. The IC50 values of Dox and GNPs-based treatments were 7.26 ± 0.4 and 22.13 ± 1.3 µg/mL, respectively. Interestingly, treatments combining Dox and GNPs together showed an IC50 value of 3.52 ± 0.1 µg/mL, indicating that they targeted cancer cells more efficiently.
Insights into the Dead Sea Transform Activity through the study of fracture-induced electromagnetic radiation (FEMR) signals before the Syrian-Turkey earthquake (Mw-6.3) on 20.2.2023
Authors: Das Shreeja , Frid Vladimir , Rabinovitch Avinoam , Bahat Dov , Kushnir Uri
Published: February 2024

Observations of fracture-induced electromagnetic radiation (FEMR) were conducted along the Dead Sea Transform (DST) from Sodom to Jericho, coinciding with a magnitude (Mw) 6.3 aftershock earthquake (EQ) in the Turkey-Syrian region on February 20, 2023. The FEMR parameters (“hits,” Benioff strain release, frequency, rise-time, energy) and associated crack dimensions were analyzed, focusing on trends leading up to the EQ. This study investigated the Benioff Strain plot and other parameters in three consecutive earthquake nucleation stages leading to the catastrophe. The first stage showed increased FEMR hits and frequency, decreased rise time (T′), and crack dimensions. In the second stage, FEMR hits and crack width decreased while other parameters continued to rise, accumulating the second-highest energy, likely due to high-stress drop. The third stage exhibited steadily increasing FEMR hits and energy and a notable increase in crack dimensions, suggesting an imminent macro failure event. The cyclic trend in FEMR hits indicates alternating periods of high activity and silence, potentially linked to stress changes during crack propagation. Taken shortly before the earthquake, these measurements offer valuable insights into how FEMR parameters vary before seismic events, bridging the gap between lab-scale studies of rock collapses under stress and large-scale failure phenomena.
Distribution and elimination kinetics of midazolam and metabolites after post-resuscitation care: a prospective observational study
Authors: Jeong Wonjoon , Sunwoo Jung , You Yeonho , Park Jung Soo , Min Jin Hong , In Yong Nam , Ahn Hong Joon , Jeon So Young , Hong Jang Hee , Song Ji Hye , Kang Hyein , Nguyen My Tuyen Thi , Kim Jaehan , Kang Changshin
Published: February 2024

Administration of sedatives for post-resuscitation care can complicate the determination of the optimal timing to avoid inappropriate, pessimistic prognostications. This prospective study aimed to investigate the distribution and elimination kinetics of midazolam (MDZ) and its metabolites, and their association with awakening time. The concentrations of MDZ and its seven metabolites were measured immediately and at 4, 8, 12, and 24 h after the discontinuation of MDZ infusion, using liquid chromatography-tandem mass spectrometry. The area under the time-plasma concentration curve from 0 to 24 h after MDZ discontinuation (AUClast) was calculated based on the trapezoidal rule. Of the 15 enrolled patients, seven awakened after the discontinuation of MDZ infusion. MDZ and three of its metabolites were major compounds and their elimination kinetics followed a first-order elimination profile. In the multivariable analysis, only MDZ was associated with awakening time (AUClast: R2 = 0.59, p = 0.03; AUCinf: R2 = 0.96, p < 0.001). Specifically, a 0.001% increase in MDZ AUC was associated with a 1% increase in awakening time. In the individual regression analysis between MDZ concentration and awakening time, the mean MDZ concentration at awakening time was 16.8 ng/mL. The AUC of MDZ is the only significant factor associated with the awakening time.
Chaotic opposition learning with mirror reflection and worst individual disturbance grey wolf optimizer for continuous global numerical optimization
Authors: Adegboye Oluwatayomi Rereloluwa , Feda Afi Kekeli , Ojekemi Opeoluwa Seun , Agyekum Ephraim Bonah , Hussien Abdelazim G. , Kamel Salah
Published: February 2024

The effective meta-heuristic technique known as the grey wolf optimizer (GWO) has shown its proficiency. However, due to its reliance on the alpha wolf for guiding the position updates of search agents, the risk of being trapped in a local optimal solution is notable. Furthermore, during stagnation, the convergence of other search wolves towards this alpha wolf results in a lack of diversity within the population. Hence, this research introduces an enhanced version of the GWO algorithm designed to tackle numerical optimization challenges. The enhanced GWO incorporates innovative approaches such as Chaotic Opposition Learning (COL), Mirror Reflection Strategy (MRS), and Worst Individual Disturbance (WID), and it’s called CMWGWO. MRS, in particular, empowers certain wolves to extend their exploration range, thus enhancing the global search capability. By employing COL, diversification is intensified, leading to reduced solution stagnation, improved search precision, and an overall boost in accuracy. The integration of WID fosters more effective information exchange between the least and most successful wolves, facilitating a successful exit from local optima and significantly enhancing exploration potential. To validate the superiority of CMWGWO, a comprehensive evaluation is conducted. A wide array of 23 benchmark functions, spanning dimensions from 30 to 500, ten CEC19 functions, and three engineering problems are used for experimentation. The empirical findings vividly demonstrate that CMWGWO surpasses the original GWO in terms of convergence accuracy and robust optimization capabilities.
Radiomics for residual tumour detection and prognosis in newly diagnosed glioblastoma based on postoperative [11C] methionine PET and T1c-w MRI
Authors: Shahzadi Iram , Seidlitz Annekatrin , Beuthien-Baumann Bettina , Zwanenburg Alex , Platzek Ivan , Kotzerke Jörg , Baumann Michael , Krause Mechthild , Troost Esther G. C. , Löck Steffen
Published: February 2024

Personalized treatment strategies based on non-invasive biomarkers have potential to improve patient management in patients with newly diagnosed glioblastoma (GBM). The residual tumour burden after surgery in GBM patients is a prognostic imaging biomarker. However, in clinical patient management, its assessment is a manual and time-consuming process that is at risk of inter-rater variability. Furthermore, the prediction of patient outcome prior to radiotherapy may identify patient subgroups that could benefit from escalated radiotherapy doses. Therefore, in this study, we investigate the capabilities of traditional radiomics and 3D convolutional neural networks for automatic detection of the residual tumour status and to prognosticate time-to-recurrence (TTR) and overall survival (OS) in GBM using postoperative [11C] methionine positron emission tomography (MET-PET) and gadolinium-enhanced T1-w magnetic resonance imaging (MRI). On the independent test data, the 3D-DenseNet model based on MET-PET achieved the best performance for residual tumour detection, while the logistic regression model with conventional radiomics features performed best for T1c-w MRI (AUC: MET-PET 0.95, T1c-w MRI 0.78). For the prognosis of TTR and OS, the 3D-DenseNet model based on MET-PET integrated with age and MGMT status achieved the best performance (Concordance-Index: TTR 0.68, OS 0.65). In conclusion, we showed that both deep-learning and conventional radiomics have potential value for supporting image-based assessment and prognosis in GBM. After prospective validation, these models may be considered for treatment personalization.
Quantitative trait loci and genomic prediction for grain sugar and mineral concentrations of cowpea [Vigna unguiculata (L.) Walp.]
Authors: Huynh Bao-Lam , Stangoulis James C. R. , Vuong Tri D. , Shi Haiying , Nguyen Henry T. , Duong Tra , Boukar Ousmane , Kusi Francis , Batieno Benoit J. , Cisse Ndiaga , Diangar Mouhamadou Moussa , Awuku Frederick Justice , Attamah Patrick , Crossa José , Pérez-Rodríguez Paulino , Ehlers Jeffrey D. , Roberts Philip A.
Published: February 2024

Development of high yielding cowpea varieties coupled with good taste and rich in essential minerals can promote consumption and thus nutrition and profitability. The sweet taste of cowpea grain is determined by its sugar content, which comprises mainly sucrose and galacto-oligosaccharides (GOS) including raffinose and stachyose. However, GOS are indigestible and their fermentation in the colon can produce excess intestinal gas, causing undesirable bloating and flatulence. In this study, we aimed to examine variation in grain sugar and mineral concentrations, then map quantitative trait loci (QTLs) and estimate genomic-prediction (GP) accuracies for possible application in breeding. Grain samples were collected from a multi-parent advanced generation intercross (MAGIC) population grown in California during 2016–2017. Grain sugars were assayed using high-performance liquid chromatography. Grain minerals were determined by inductively coupled plasma–optical emission spectrometry and combustion. Considerable variation was observed for sucrose (0.6–6.9%) and stachyose (2.3–8.4%). Major QTLs for sucrose (QSuc.vu-1.1), stachyose (QSta.vu-7.1), copper (QCu.vu-1.1) and manganese (QMn.vu-5.1) were identified. Allelic effects of major sugar QTLs were validated using the MAGIC grain samples grown in West Africa in 2017. GP accuracies for minerals were moderate (0.4–0.58). These findings help guide future breeding efforts to develop mineral-rich cowpea varieties with desirable sugar content.
Longitudinal antibody dynamics after COVID-19 vaccine boosters based on prior infection status and booster doses
Authors: Matsumoto Naomi , Sasaki Ayako , Kadowaki Tomoka , Mitsuhashi Toshiharu , Takao Soshi , Yorifuji Takashi
Published: February 2024

Global concern over COVID-19 vaccine distribution disparities highlights the need for strategic booster shots. We explored longitudinal antibody responses post-booster during the Omicron wave in a Japanese cohort, emphasizing prior infection and booster doses. This prospective cohort study included 1763 participants aged 18 years and older with at least three vaccine doses (7376 datapoints). Antibody levels were measured every 2 months. We modeled temporal declines in antibody levels after COVID-19 vaccine boosters according to prior infection status and booster doses using a Bayesian linear mixed-effects interval-censored model, considering age, sex, underlying conditions, and lifestyle. Prior infection enhanced post-booster immunity (posterior median 0.346, 95% credible interval [CrI] 0.335–0.355), maintaining antibody levels (posterior median 0.021; 95% CrI 0.019–0.023) over 1 year, in contrast to uninfected individuals whose levels had waned by 8 months post-vaccination. Each additional booster was correlated with higher baseline antibody levels and slower declines, comparing after the third dose. Female sex, older age, immunosuppressive status, and smoking history were associated with lower baseline post-vaccination antibodies, but not associated with decline rates except for older age in the main model. Prior infection status and tailored, efficient, personalized booster strategies are crucial, considering sex, age, health conditions, and lifestyle.
Dual-layer detector spectral CT-based machine learning models in the differential diagnosis of solitary pulmonary nodules
Authors: Lu Hui , Liu Kaifang , Zhao Huan , Wang Yongqiang , Shi Bo
Published: February 2024

The benign and malignant status of solitary pulmonary nodules (SPNs) is a key determinant of treatment decisions. The main objective of this study was to validate the efficacy of machine learning (ML) models featured with dual-layer detector spectral computed tomography (DLCT) parameters in identifying the benign and malignant status of SPNs. 250 patients with pathologically confirmed SPN were included in this study. 8 quantitative and 16 derived parameters were obtained based on the regions of interest of the lesions on the patients’ DLCT chest enhancement images. 6 ML models were constructed from 10 parameters selected after combining the patients' clinical parameters, including gender, age, and smoking history. The logistic regression model showed the best diagnostic performance with an area under the receiver operating characteristic curve (AUC) of 0.812, accuracy of 0.813, sensitivity of 0.750 and specificity of 0.791 on the test set. The results suggest that the ML models based on DLCT parameters are superior to the traditional CT parameter models in identifying the benign and malignant nature of SPNs, and have greater potential for application.
Optimizing grid-connected PV systems with novel super-twisting sliding mode controllers for real-time power management
Authors: Mohapatra Bhabasis , Sahu Binod Kumar , Pati Swagat , Bajaj Mohit , Blazek Vojtech , Prokop Lukas , Misak Stanislav
Published: February 2024

Over the past years, the use of renewable energy sources (RESs) has grown significantly as a means of providing clean energy to counteract the devastating effects of climate change. Reducing energy costs and pollution have been the primary causes of the rise in solar photovoltaic (PV) system integrations with the grid in recent years. A load that is locally connected to a GCPV requires both active and reactive power control. In order to control both active and reactive power, MAs and advanced controllers are essential. Researchers have used one of the recently developed MAs, known as the CAOA, which is based on mathematical arithmetic operators to tackle a few real-world optimization problems. Some disadvantages of CAOA include its natural tendency to converge to a local optimum and its limited capacity for exploration. By merging the PSO and CAOA methodologies, this article suggests the IAOA. To show how applicable IAOA is, its performance has been evaluated using four benchmark functions. The implementation of an IAOA-based ST-SMC for active and reactive power control is addressed in this article, which offers an innovative approach of research. In comparison to PSO-based ST-SMC and CAOA-based ST-SMC, the proposed IAOA-based ST-SMC appears to be superior, with settling time for active and reactive power control at a minimum of 0.01012 s and 0.5075 s. A real-time OPAL-RT 4510 simulator is used to validate the performance results of a 40 kW GCPV system after it has been investigated in the MATLAB environment.
The role of farming and fishing in the rise of social complexity in the Central Andes: a stable isotope perspective
Authors: Pezo-Lanfranco Luis , Colonese André Carlo
Published: February 2024

For many years, the rise of stratified societies along the Central Andean coast, known as the birthplace of Andean civilization, has been closely linked to a marine-oriented economy. This hypothesis has recently been challenged by increasing evidence of plant management and cultivation among Andean populations long before the emergence of complex societies and monumental architecture. The extent to which marine and plant-based economies were integrated and their contributions to early sedentism, population growth, and intra-community stratification, however, remain subjects of ongoing and contentious debate. Using Bayesian Mixing Models we reanalyze the previously published stable isotopes (δ15Ncollagen, δ13Ccollagen, δ13Capatite) values of 572 human individuals from 39 archaeological sites in the Central Andes dated between ca. 7000 BCE and 200 CE to reconstruct dietary regimes in probabilistic terms. Our results reveal that fish, terrestrial fauna, and cultivated plants variably contributed to the diet of prehistoric Andean populations; in coastal and middle valley settlements plant cultivation, not fishing, fueled the development of the earliest complex societies during the Formative Period (from 3000 BCE). Similarly, in the highlands the societies that built ceremonial centers show a plant-based economy. Our findings also show that maize only became a staple food (> 25% dietary contribution) in more recent phases of Andean prehistory, around 500 BCE.
Hybrid quantum-classical polarizability model for single molecule biosensing
Authors: Zossimova Ekaterina , Fiedler Johannes , Vollmer Frank , Walter Michael
Published: February 2024

We present a 3-layer cavity model to calculate the polarizability of solvated molecules. By analogy, the different layers of our cavity model resemble the nested structure of a Matryoshka doll.
Engineering strong man-made cellulosic fibers: a review of the wet spinning process based on cellulose nanofibrils
Authors: Zhang Zihuan , Kong Yuying , Gao Junqi , Han Xiao , Lian Zechun , Liu Jiamin , Wang Wen-Jun , Yang Xuan
Published: February 2024

This review aims to summarize the timely progress of manufacturing high-performance nanocellulose-based fibers using wet spinning process.
Sphingomyelinase-responsive nanomicelles for targeting atherosclerosis
Authors: Muñoz-Hernando María , Nogales Paula , Fernández-Barahona Irene , Ruiz-Cabello Jesús , Bentzon Jacob F. , Herranz Fernando
Published: February 2024

Sphingomyelinase enzymatic activity destabilises iron oxide nanomicelles and promotes its accumulation in atherosclerosis in vivo.
Novel nickel(ii) phthalocyanine/reduced graphene oxide: an electrochemical sensing platform for analysis of hydroquinone and chloramphenicol in environmental samples
Authors: Mounesh  , Manikanta P. , Nikam Rohit Rangnath , Tigari Girish , Nagaraja Bhari Mallanna
Published: February 2024

The novel nickel(ii) phthalocyanine (NiTBPBXCAPc) and rGO were confirmed by spectroscopic and microscopic method. The NiTBPBXCAPc@rGO nanocomposite has been developed for sensitive and selective detection of hydroquinone and chloramphenicol.
Surface active functional groups enhanced PET non‐woven fabric for the filtering of harmful substances in smoke
Authors: Ning Lu , Tang Pengfei , Lu Xiong , Yang Guangyuan , Jiang Faxing , Zhang Hongping
Published: February 2024

Harmful components in cigarette smoke, such as nicotine, tar, and organic particulate matter, are the primary culprits behind lung diseases. While conventional filter materials based on cellulose, carbon, and molecular sieves exhibit commendable filtration capabilities, their high cost restricts their widespread applications. Based on this, the authors aim to prepare PET‐based filter materials with good adsorption properties through a simple surface functionalisation strategy. The adsorption performance of the PET‐based non‐woven fabric was enhanced by the introduction of sodium alginate (SA). The gas adsorption experiments results reveal that SA‐modified PET (SA‐PET) exhibits significantly improved filtration efficiency for nicotine, tar, and total particulate matter—increasing by 27.1%, 26.2%, and 21.3%, respectively. Moreover, SA‐PET exhibits more odour control ability than traditional activated carbon‐based filter materials. These results prove that surface‐functionalised SA‐PET has better filtration performance for harmful substances in smoke and provides a new strategy for the design of high‐performance filtration materials.
Knowledge graph reasoning for cyber attack detection
Authors: Gilliard Ezekia , Liu Jinshuo , Aliyu Ahmed Abubakar
Published: February 2024

In today's digital landscape, cybercriminals are constantly evolving their tactics, making it challenging for traditional cybersecurity methods to keep up. To address this issue, this study explores the potential of knowledge graph reasoning as a more adaptable and sophisticated approach to identify and counter network attacks. By leveraging graph structures imbued with human‐like thinking, this method enhances the resilience of cybersecurity systems. The study focuses on three critical aspects: data preparation, semantic foundations, and knowledge graph inference techniques. Through an in‐depth analysis of these components, the research aims to reveal how knowledge graph reasoning can improve cyberattack detection and enhance the overall efficacy of cybersecurity measures, including intrusion detection systems. The proposed approach has undergone extensive experimentation to validate its effectiveness compared to existing methods. The results of the experiment have shown a remarkable advancement in accuracy, speed, and recall for recognition, surpassing current methods. This achievement is a notable contribution in the realm of managing big data in cybersecurity. The study establishes a foundation for the automation of network attack detection, ultimately enhancing overall network security.
Towards efficient traffic crash detection based on macro and micro data fusion on expressways: A digital twin framework
Authors: Qu Qikai , Shen Yongjun , Yang Miaomiao , Zhang Rui
Published: February 2024

Efficient detection of traffic crashes has been a significant matter of concern with regards to expressway safety management. The current challenge is that, despite collecting vast amounts of data, expressway detection equipment is plagued by low data utilization rates, unreliable crash detection models, and inadequate real‐time updating capabilities. This study is to develop an effective digital twin framework for the detection of traffic crashes on expressways. Firstly, the digital twin technology is used to create a virtual entity of the real expressway. A fusion method for macro and micro traffic data is proposed based on the location of multi‐source detectors on a digital twin platform. Then, a traffic crash detection model is developed using the ThunderGBM algorithm and interpreted by the SHAP method. Furthermore, a distributed strategy for detecting traffic crashes is suggested, where various models are employed concurrently on the digital twin platform to enhance the general detection ability and reliability of the models. Finally, the efficacy of the digital twin framework is confirmed through a case study of certain sections of the Nanjing Ring expressway. This study is expected to lay the groundwork for expressway digital twin studies and offer technical assistance for expressway traffic management.
Crocus sativus updated
Authors: Chrubasik-Hausmann Sigrun
Published: February 2024

Die goldgelben Stigmen des Safrans werden seit der Antike nicht nur für
Kultzwecke und zum Färben, sondern auch als Heilmittel genutzt. Der
Beitrag stellt relevante Forschungsergebnisse der letzten Jahre bei
verschiedenen Indikationen vor.
What factors will affect the effectiveness of using ChatGPT to solve programming problems? A quasi-experimental study
Authors: Jing Yuhui , Wang Haoming , Chen Xiaojiao , Wang Chengliang
Published: February 2024

The emergence of ChatGPT has sparked new expectations for AI-empowered educational transformation. However, it remains unknown which factors affect its effectiveness in empowering learners to solve programming problems. Therefore, this study employed a quasi-experimental research design and used Python graphing in programming education as an example to investigate the factors influencing the effectiveness of learners in applying ChatGPT to problem-solving. Findings: AI literacy significantly influences learners’ effectiveness in using ChatGPT to solve problems, with AI awareness and AI usage being key factors. The knowledge base of programming language significantly affects learners’ effectiveness in applying ChatGPT to solve programming problems. Learners’ cognitive level of ChatGPT significantly influences their effectiveness in applying ChatGPT to problem-solving, while usage intention does not have a significant impact. However, learners’ intention to use ChatGPT significantly improves after application. Based on these findings, this study proposes that in the process of empowering education with Artificial Intelligence Generated Content (AIGC) products, the focus on learners should shift from cultivating their AI usage to AI literacy, laying the foundation for empowering learning with AIGC products. It is suggested to shift from mastering specific knowledge to graph-based rules as a method for empowering learning with AIGC products. Additionally, the focus should shift from enhancing learners’ intention to use the technology to strengthen their technological awareness, thereby creating practical pathways for empowering learning with AIGC products.
Contextual beamforming: Exploiting location and AI for enhanced wireless telecommunication performance
Authors: Kaur Jaspreet , Bhatti Satyam , Tan Kang , Popoola Olaoluwa R. , Imran Muhammad Ali , Ghannam Rami , Abbasi Qammer H. , Abbas Hasan T.
Published: February 2024

Beamforming, an integral component of modern mobile networks, enables spatial selectivity and improves network quality. However, many beamforming techniques are iterative, introducing unwanted latency to the system. In recent times, there has been a growing interest in leveraging mobile users’ location information to expedite beamforming processes. This paper explores the concept of contextual beamforming, discussing its advantages, disadvantages, and implications. Notably, we demonstrate an impressive 53% improvement in the signal-to-interference-plus-noise ratio by implementing the adaptive beamforming maximum ratio transmission (MRT) algorithm compared to scenarios without beamforming. It further elucidates how MRT contributes to contextual beamforming. The importance of localization in implementing contextual beamforming is also examined. Additionally, the paper delves into the use of artificial intelligence (AI) schemes, including machine learning and deep learning, in implementing contextual beamforming techniques that leverage user location information. Based on the comprehensive review, the results suggest that the combination of MRT and zero-forcing techniques, alongside deep neural networks employing Bayesian optimization, represents the most promising approach for contextual beamforming. Furthermore, the study discusses the future potential of programmable switches, such as Tofino—an innovative switch developed by Barefoot Networks (now a part of Intel)—in enabling location-aware beamforming. This paper highlights the significance of contextual beamforming for improving wireless telecommunications performance. By capitalizing on location information and employing advanced AI techniques, the field can overcome challenges and unlock new possibilities for delivering reliable and efficient mobile networks.
Conserving the Pilbara leaf-nosed bat: directions for future research and management
Authors: Bradley Holly S. , Armstrong Kyle N. , Bullen Robert D. , Ellis Ryan , Knuckey Chris G. , Ottewell Kym , Reiffer Scott , Somaweera Ruchira , Umbrello Linette , van Leeuwen Stephen
Published: February 2024

The Pilbara leaf-nosed bat (Rhinonicteris aurantia ‘Pilbara form’) is a threatened insectivorous microbat endemic to the Pilbara region of Western Australia. It is at risk of significant population decline, particularly due to habitat loss from mining. To address its key threats, stakeholders from a range of backgrounds collectively listed and prioritised research actions in 2013. This exercise was repeated in 2022 to evaluate and update progress of the research priorities. We conducted a review of scientific and grey literature (2013–2023) to: (1) identify the work undertaken to date that addressed the research priorities identified in the 2013 stakeholder workshop; (2) identify the current knowledge gaps in Pilbara leaf-nosed bat ecology, conservation, and threatening processes; and (3) highlight how these gaps relate to the newly ranked 2022 priority list for both research and management outcomes. We found that the 2013 research priorities were largely unaddressed, with most publications and unpublished industry reports in the review period primarily reporting presence or monitoring data around areas of interest to the resources sector, with minimal focus on the species’ conservation or management directly. Therefore, the knowledge gaps identified in 2013 were still largely relevant in 2022. Further targeted research is required to meet the 2022 priorities and better understand the habitat characteristics, movement ecology, disturbance buffer requirements, and cumulative impacts of mining on Pilbara leaf-nosed bat colonies. Overall, targeted research beyond traditional mining outputs, changes to regulatory procedure, and collaborative, adaptive management, are key to supporting the long-term persistence of Pilbara leaf-nosed bats.
The role of the oviduct environment in embryo survival
Authors: Juengel Jennifer L. , Reader Karen L. , Maclean Paul H. , Quirke Laurel D. , Zellhuber-McMillan Sylvia , Haack Neville A. , Heiser Axel
Published: February 2024

Context Declining fertility is an issue in multiple mammalian species. As the site of fertilisation and early embryo development, the oviduct plays a critical role in embryo survival, yet there is a paucity of information on how the oviduct regulates this process. Aims We hypothesised that differences in steroid hormone signalling and/or immune function would be observed in a model of poor embryo survival, the peripubertal ewe. Methods We examined expression of steroid hormones in systemic circulation, oviductal expression of oestrogen receptor α and genes important in steroid hormone signalling, and immune function in pregnant and cyclic peripubertal and adult ewes on day 3 after oestrus. Key results Concentrations of progesterone, but not oestradiol, were decreased in the peripubertal ewe compared to the adult ewe. Oestrogen receptor α protein expression was increased in the peripubertal ewe, but pathway analysis of gene expression revealed downregulation of the oestrogen signalling pathway compared to the adult ewe. Differential expression of several genes involved in immune function between the peripubertal and adult ewe was consistent with an unfavourable oviductal environment in the peripubertal ewe lamb. Oestradiol concentration was positively correlated with the expression of multiple genes involved in the regulation of immune function. Conclusions Differences in the immune environment of the oviduct, potentially linked to differential modulation by steroid hormones, may partially underly the poor fertilisation and early embryo survival observed in the peripubertal ewe. Implications A unfavourable oviductal environment may play an important role in limiting reproductive success.
Dinickel enzyme evolved to metabolize the pharmaceutical metformin and its implications for wastewater and human microbiomes
Authors: Tassoulas Lambros J. , Rankin Joel A. , Elias Mikael H. , Wackett Lawrence P.
Published: February 2024

Metformin is the first-line treatment for type II diabetes patients and a pervasive pollutant with more than 180 million kg ingested globally and entering wastewater. The drug’s direct mode of action is currently unknown but is linked to effects on gut microbiomes and may involve specific gut microbial reactions to the drug. In wastewater treatment plants, metformin is known to be transformed by microbes to guanylurea, although genes encoding this metabolism had not been elucidated. In the present study, we revealed the function of two genes responsible for metformin decomposition (mfmAandmfmB) found in isolated bacteria from activated sludge. MfmA and MfmB form an active heterocomplex (MfmAB) and are members of the ureohydrolase protein superfamily with binuclear metal-dependent activity. MfmAB is nickel-dependent and catalyzes the hydrolysis of metformin to dimethylamine and guanylurea with a catalytic efficiency (kcat/KM) of 9.6 × 103M−1s−1and KMfor metformin of 0.82 mM. MfmAB shows preferential activity for metformin, being able to discriminate other close substrates by several orders of magnitude. Crystal structures of MfmAB show coordination of binuclear nickel bound in the active site of the MfmA subunit but not MfmB subunits, indicating that MfmA is the active site for the MfmAB complex. Mutagenesis of residues conserved in the MfmA active site revealed those critical to metformin hydrolase activity and its small substrate binding pocket allowed for modeling of bound metformin. This study characterizes the products of themfmABgenes identified in wastewater treatment plants on three continents, suggesting that metformin hydrolase is widespread globally in wastewater.
Live music stimulates the affective brain and emotionally entrains listeners in real time
Authors: Trost Wiebke , Trevor Caitlyn , Fernandez Natalia , Steiner Florence , Frühholz Sascha
Published: February 2024

Music is powerful in conveying emotions and triggering affective brain mechanisms. Affective brain responses in previous studies were however rather inconsistent, potentially because of the non-adaptive nature of recorded music used so far. Live music instead can be dynamic and adaptive and is often modulated in response to audience feedback to maximize emotional responses in listeners. Here, we introduce a setup for studying emotional responses to live music in a closed-loop neurofeedback setup. This setup linked live performances by musicians to neural processing in listeners, with listeners’ amygdala activity was displayed to musicians in real time. Brain activity was measured using functional MRI, and especially amygdala activity was quantified in real time for the neurofeedback signal. Live pleasant and unpleasant piano music performed in response to amygdala neurofeedback from listeners was acoustically very different from comparable recorded music and elicited significantly higher and more consistent amygdala activity. Higher activity was also found in a broader neural network for emotion processing during live compared to recorded music. This finding included observations of the predominance for aversive coding in the ventral striatum while listening to unpleasant music, and involvement of the thalamic pulvinar nucleus, presumably for regulating attentional and cortical flow mechanisms. Live music also stimulated a dense functional neural network with the amygdala as a central node influencing other brain systems. Finally, only live music showed a strong and positive coupling between features of the musical performance and brain activity in listeners pointing to real-time and dynamic entrainment processes.
The utility of (political) dogwhistles – a life cycle perspective
Authors: Sayeed Asad , Breitholtz Ellen , Cooper Robin , Lindgren Elina , Rettenegger Gregor , Rönnerstrand Björn
Published: February 2024

The term dogwhistle refers to an expression conveying a message to a subset of an audience which is not perceived by the rest of the group, in addition to a primary meaning directed at the group at large. We follow up on previous work in linguistics and political communication on defining dogwhistles, taking into account how they likely function in real-life political contexts. We consider the utility of dogwhistles in terms of their sensitivity and their specificity, which allows us to consider dogwhistles in terms of an idealized “life cycle”, whose phases we describe in terms of a multi-dimensional utility tradeoff, described in terms of dogwhistle users, the benefit they expect to receive from dogwhistling, and the deniability of controversial dogwhistle meanings. We propose an approach for the longitudinal study of dogwhistles, and describe the first stages of an experiment to characterize dogwhistles in terms of their lexical properties.
Islam and Politics in Asia
Authors: Hefner Robert W.
Published: February 2024

Muslim politics everywhere takes varied forms, but it is especially diverse across the geographic expanse that constitutes East, South, and Southeast Asia. Although in a few areas of South Asia Muslim polities were established during the first wave of Islamic expansion in the 7th century, Islam across most of this region arrived centuries later and through channels other than military conquest. From the late 19th century onward, the spread of capitalist modes of production, the rise of nationalist movements, and the development of new social media and new traditions of learning compounded the diversity of Muslim politics. Although some varieties of Islamic reform have sought to contain or eliminate this diversity, Muslim politics across the Asian region remains highly varied. The diversity has been compounded by Muslims’ engagements with the nation-state, capitalist development, and new practices of religious learning, association, and communications.
Legal Pluralism in Myanmar
Authors: Kyed Helene Maria
Published: February 2024

Myanmar (Burma) is characterized by a strong degree of legal pluralism, understood as the existence of more than one set of binding rules and normative orders for regulating society. Disputes and crimes are resolved by a plurality of actors and justice systems, and state law is but one among many other sets of rules and norms for defining wrongdoing and remedies. The plural legal landscape in Myanmar derives only partly from the diversity of ethnicities and customs dating back to pre-colonial times. More importantly, colonial reification of ethnic divisions and postcolonial armed conflicts and military state authoritarianism have shaped and consolidated justice systems that operate in parallel to and often in competition with the state-legal system. Empirical research and surveys conducted since the political opening in 2015 amply demonstrate that ordinary Myanmar citizens and denizens prefer to resolve disputes and crimes at the lowest level possible, predominantly within their own ethnic group and without the involvement of the state-legal system. This preference is caused by a mixture of political-historical, socioeconomic, and cultural-religious factors. Mistrust in the state’s willingness to serve the justice needs of ordinary people and discomfort with the formalistic procedures and punitive justice applied in state courts draw people toward using local justice system that apply reconciliatory and compensational justice. These local systems are also more in line with cultural and religiously informed perceptions of wrongdoing and justice. Despite the strong role of local justice systems, these are not recognized by state law. The decades of armed conflict between the military state and ethnic armed organizations have also given way to the development of more state-like, hierarchically ordered ethnic justice systems and laws, which are applied by the ethnic armed organizations in the areas they nominally control.
Landscape and Nation in North Korea
Authors: Winstanley-Chesters Robert
Published: February 2024

In 2023, images emerged of Kim Jong Un hand in hand with his young daughter Kim Ju Ae. As they walked over concrete launchpads, away from an intercontinental ballistic missile readied for launch, the leader and his child not only made a statement about succession and military power but also became a new addition to the visual vocabulary of North Korean landscapes. North Korean landscapes and geographies have held both an energetic, vibrant piquancy and a curious, opaque mysteriousness for the outsider almost since the nation’s foundation in 1948. Observers are confronted with a commonality of visual and semiotic tropes focused on the materiality of North Korean spaces; these include barren hills and fields, missiles spewing fire as they launch out of their silos or from their transporters, massed ranks of soldiers marching in steps of uncanny synchrony, starving children, mass hysteria at the death of an autocrat, and the infrastructure of illicit nuclear capacity. North Korean landscapes are real and unreal; known, unknown, and unknowable; constructed and mythographic; a mélange and intersection of fears, history, threat, and ambition. Thongchai Winichakul in his articulation of the geo-body, explored the active and engaged roles that landscape, space, and topography play in the formation of a nation and a national body. Seen in such a frame, North Korea seems to possess a mirrored double: landscapes that play key roles in the nation’s prehistory and foundation are central to its emergent period and are reflective of and enmeshed in the state’s ideological projections. At the same time, for the outsider, the geo-body of North Korea reflects the bodies of its people as they are seen—as stunted, denuded, oppressed, and incarcerated. A holistic overview of North Korean landscapes must move between the mythic and the material, the imagined and the encountered, dualistic in essence and dependent on a viewer’s predictions and presumptions, placing two very different terrains in energetic tension.
The Horse in Southern Africa
Authors: Mitchell Peter
Published: February 2024

Horses are not native to southern Africa. They were introduced there by European settlers, principally the Dutch, who brought them to their new base at Cape Town in 1653. Although keeping horses was constrained by diseases against which the animals had no immunity, notably African horse sickness, equine piroplasmosis, and trypanosomiasis, horses played a crucial role in facilitating European expansion into the southern African interior. Horses were not, however, always under European control. In several instances, Indigenous populations, often of creolized descent, used them to maintain raiding, hunting, and pastoralist lifestyles of their own. Along with the Korana in central South Africa and the Oorlam and Herero in Namibia, the best-documented of these groups were the AmaTola “Bushmen,” who operated in the Maloti-Drakensberg Mountains of highland Lesotho in the mid-19th century. Subsequently, horses were a crucial resource to both British and Afrikaner forces during the Second South African War (1899–1902), a conflict that helped encourage a more favorable view of the animals used in warfare, and in later 20th-century counterinsurgency operations. Additionally, from the moment of their introduction to the region and continuing right through the apartheid era, horses were significant in delineating and reinforcing distinctions of class, race, and wealth via restrictions on who could ride, keep, or race them, as well as through the rearing and creation of specific breeds with specific ethnic or social associations.
Application of One Health Principles to the Control of Antimicrobial Resistance
Authors: Davis Meghan F.
Published: February 2024

One Health interventions that address human, animal, and environmental health domains are critical for controlling the global challenge of antimicrobial resistance (AMR). These interventions can target upstream conditions, such as prevention strategies like vaccination or policies, to restrict antimicrobial use in humans, animals, and plants, with a goal to reduce the selective pressure that can drive the emergence and expansion of drug-resistant pathogens. Downstream, environmental hygiene initiatives can target transmission pathways between people and animals to limit exposure to drug-resistant pathogens. Holistic, transdisciplinary approaches that address the factors driving antimicrobial use in people, animals, and the environment hold promise to help curb the global challenge of AMR.
Female Slaveholders in British America
Authors: Walker Christine
Published: February 2024

Women actively contributed to the expansion of chattel slavery in British America. During the colonial era, female inhabitants living in every region claimed by Britain, from the northernmost colonies to the southernmost islands in the Caribbean, held other people in bondage. As enslavers, women exercised their authority over captives in various capacities. Female slaveholders treated enslaved people as personal property that could be bought, sold, or rented out in the marketplace. They commanded enslaved people to perform diverse types of labor. Some worked in households as servants, cooks, and laundresses, while others labored in taverns, shops, fields, and on waterways. Women also bequeathed captives to descendants, often preferring to transfer enslaved people along female lines. Inheritance became an important mechanism for women to maintain control of, and benefit from, slaveholding. Finally, women exercised their authority by subjecting enslaved people to a spectrum of abuses ranging from corporeal punishment, imprisonment, and transportation, to starvation and execution. Early modern gender inequalities intensified women’s participation in slavery, offering them an alternative form of support, profit, and command. By offsetting the economic, legal, and social limitations imposed by patriarchal societies, slaveholding thus empowered women.
Japanese Immigrants and the History of Rice in California
Authors: Tokunaga Yu
Published: February 2024

The cultivation of California rice began in 1909 when a Japanese agricultural engineer succeeded in growing short-grain Japonica rice varieties in Butte County. With commercial cultivation starting in 1912, rice fields rapidly expanded across Northern California. Japanese immigrants, however, continued to eat short-grain rice imported from Japan with a strong sense of affection. This situation dramatically changed in 1918, at around the end of World War I. The war led to an expansion of demand for food worldwide and a serious shortage of rice in Japan, resulting in the steep rise of rice prices and the Kome Sōdō (Rice Riots). The Japanese government decided to ban Japanese rice exports to prevent further inflation and solve the food shortage problem in Japan. This policy marked a turning point from which Japanese immigrants in the mainland United States began to mainly eat California rice. It also sparked serious debates among the Japanese who had heavily relied on Japanese-grown rice for their daily diet, forcing them to redefine their permanent residence in the United States not simply as a place to live but also as the land that provided them with their major source of nutrients. In the 1920s, California rice became a staple for ethnic Japanese residents and an export item to their homeland. This series of changes marked an important period in a history in which the Japanese immigrant experience intersected with the development of US agriculture and the circulation of food around the Pacific Ocean. The history of California rice from the 1900s to the 1930s reveals the shifting US-Japan trade relations as well as the transnational process in which food kept Japanese immigrants culturally connected to the homeland while further rooting them to life in the United States as permanent residents and consumers of California rice.