bluuebunny/crossref_metadata_2025 huggingface dataset:
Rescue of morphological defects in
Streptomyces venezuelae
by the alkaline volatile compound trimethylamine
Authors: Zhu Yanping , Zeng Yanhong , Liu Meng , Lu Ting , Pang Xiuhua
Published: August 2024

Microorganisms can produce a vast diversity of volatile organic compounds of different chemical classes that are capable of mediating intra- and inter-kingdom interactions. In this study, we showed that the soil-dwelling bacterium
Streptomyces venezuelae
can produce alkaline volatiles under multiple growth conditions, which we discovered through investigation of the
S. venezuelae
mutant strain MU-1. Strain MU-1 has a defective morphology and exhibits a bald phenotype due to the lack of aerial mycelia and spores, as confirmed by scanning electron microscopy. Using physical barriers to separate the strains on culture plates, we determined that volatile compounds produced by wild-type
S. venezuelae
could rescue the phenotype of strain MU-1, and pH analysis of the growth medium indicated that these volatile compounds were alkaline. Ultra-high-performance liquid chromatography, combined with mass spectrometry analysis, showed that wild-type
S. venezuelae
produced abundant levels of the alkaline volatile trimethylamine (TMA) and the oxide form TMAO; however, the levels of these compounds were much lower in strain MU-1. Notably, exposure to TMA alone could rescue the phenotype of this mutant strain, restoring the production of aerial mycelia and spores. We also showed that the rescue effect by alkaline volatiles is mostly species-specific, suggesting that the volatiles may aid particular mutants or other less-fit variants of closely related species to resume normal physiological status and to compete more effectively in complex communities such as soil. Our study reveals a new and intriguing role for bacterial volatiles, including volatiles that may have toxic effects on other species.

IMPORTANCE

Bacterial volatiles have a wide range of biological roles at intra- or inter-kingdom levels. The impact of volatiles has mainly been observed between producing bacteria and recipient bacteria, mostly of different species. In this study, we report that the wild-type, soil-dwelling bacterium
Streptomyces venezuelae
, which forms aerial hypha and spores as part of its normal developmental cycle, also produces the alkaline volatile compound trimethylamine (TMA) under multiple growth conditions. We showed that the environmental dispersion of TMA produced by
S. venezuelae
promotes the growth and differentiation of growth-deficient mutants of the same species or other slowly growing
Streptomyces
bacteria, and thus aids in their survival and their ability to compete in complex environmental communities such as soil. Our novel findings suggest a potentially profound biological role for volatile compounds in the growth and survival of communities of volatile-producing
Streptomyces
species.
Stratigraphic record of tectonic and climatic impact on orogenic growth: An example from the Hexi Corridor Basin, NE Tibetan Plateau
Authors: Pan Baotian , Zhang Jian , Geng Haopeng , Saylor Joel , Cheng Feng , Chen Dianbao , Li Lin , Xu Ziyi , Jian Liwei , Nie Junsheng
Published: August 2024

The locus of shortening, accretion, and erosion are key components in modulating the rate, pattern, and magnitude of orogenic wedge growth, but separating their respective roles in the evolution of wedge taper is often difficult because of the absence of exhumation and uplift data from the mountains. However, such information can be preserved in the adjacent basins, and a combination of sediment provenance and accumulation rate records may be able to distinguish tectonic versus climatically caused orogenic wedge evolution. Here we present a joint sediment accumulation rate (SAR) and provenance analysis based on zircon U-Pb ages and heavy mineral composition of a drill core from the foreland of the Qilian Shan (i.e., Hexi Corridor Basin, NE Tibetan Plateau) with the aim to reveal the evolution of the Qilian orogenic wedge and its relationship to tectonics and climate. The provenance data show a gradual increase in sediment attributable to the Yumu Shan in the toe of the orogenic wedge and associated decrease in contribution from the high-elevation hinterland Zoulang Nan Shan source between 7 Ma and 3 Ma, followed by a reverse of these trends from 3 Ma to the modern. The increased contribution from the toe of the orogenic wedge (Yumu Shan) is accompanied by an increase in SAR, and we interpret this joint signal as the result of in-sequence thrusting, which caused flexural subsidence and created more deposition space in the bounding foreland. The increased contribution from the hinterland from 3.0 Ma to 1.8 Ma, accompanied with the decreased SAR, is attributed to the onset of Northern Hemisphere glaciation, which increased glacial erosion of the high-elevation hinterland areas and caused erosional unloading of the orogenic wedge, leading to flexural uplift in the foreland and reduced SAR. After 1.8 Ma, continued increase in the contribution from the hinterland accompanied with the SAR increase is less straightforward to interpret. We suspect that glacial erosion might have activated fault movements in the hinterland area, and tectonic-caused rock uplift was faster than glacial erosion. Therefore, high sediment flux from the hinterland was maintained but flexural subsidence accelerated. Our results demonstrate that both tectonics and climate have shaped regional landscape evolution and emphasize the role of glacial erosion in accounting for orogenic wedge evolution at ca. 3 Ma.
Unusual clinical presentation, microscopy and immunohistochemistry of oral pyogenic granuloma in a paediatric patient
Authors: Amritha Rajeswary , Rahul Morankar , Jot Kiran , Tewari Nitesh
Published: August 2024

An unusual clinical presentation of any pathology prompts a diagnostic dilemma, which further brings challenges in treatment planning. Pyogenic granuloma (microscopically lobular capillary haemangioma) is a benign vascular tumour that commonly involves the skin and mucous membranes and usually manifests as a solitary papule with a friable pedunculated base. Rapid exophytic growth and an ulcerated surface with bleeding on provocation are characteristic, with a gingival predominance for the site. This case report aims to elaborate on an unusual clinical presentation of oral pyogenic granuloma in a middle-childhood female patient. The clinical and radiographic characteristics of the lesion were unremarkable to the diagnosis but rather mimicked other intraoral lesions. It is histopathology that could solve the puzzle with the microscopic and immunohistochemical findings that rendered the final diagnosis of lobular capillary haemangioma.
Prognostic value of the 5-SENSE Score to predict focality of the seizure-onset zone as assessed by stereoelectroencephalography: a prospective international multicentre validation study
Authors: Astner-Rohracher Alexandra , Ho Alyssa , Archer John , Bartolomei Fabrice , Brazdil Milan , Cacic Hribljan Melita , Castellano James , Dolezalova Irena , Fabricius Martin Ejler , Garcés-Sanchez Mercedes , Hammam Kahina , Ikeda Akio , Ikeda Kristin , Kahane Philippe , Kalamangalam Giridhar , Kalss Gudrun , Khweileh Mays , Kobayashi Katsuya , Kwan Patrick , Laing Joshua Andrew , Leitinger Markus , Lhatoo Samden , Makhalova Julia , McGonigal Aileen , Mindruta Iona , Mizera Mary Margaret , Neal Andrew , Oane Irina , Parikh Prachi , Perucca Piero , Pizzo Francesca , Rocamora Rodrigo , Ryvlin Philippe , San Antonio Arce Victoria , Schuele Stephan , Schulze-Bonhage Andreas , Suller Marti Ana , Urban Alexandra , Villanueva Vincente , Vilella Bertran Laura , Whatley Benjamin , Beniczky Sandor , Trinka Eugen , Zimmermann Georg , Frauscher Birgit
Published: August 2024

Introduction

Epilepsy surgery is the only curative treatment for patients with drug-resistant focal epilepsy. Stereoelectroencephalography (SEEG) is the gold standard to delineate the seizure-onset zone (SOZ). However, up to 40% of patients are subsequently not operated as no focal non-eloquent SOZ can be identified. The 5-SENSE Score is a 5-point score to predict whether a focal SOZ is likely to be identified by SEEG. This study aims to validate the 5-SENSE Score, improve score performance by incorporating auxiliary diagnostic methods and evaluate its concordance with expert decisions.

Methods and analysis

Non-interventional, observational, multicentre, prospective study including 200 patients with drug-resistant epilepsy aged ≥15 years undergoing SEEG for identification of a focal SOZ and 200 controls at 22 epilepsy surgery centres worldwide. The primary objective is to assess the diagnostic accuracy and generalisability of the 5-SENSE in predicting focality in SEEG in a prospective cohort. Secondary objectives are to optimise score performance by incorporating auxiliary diagnostic methods and to analyse concordance of the 5-SENSE Score with the expert decisions made in the multidisciplinary team discussion.

Ethics and dissemination

Prospective multicentre validation of the 5-SENSE score may lead to its implementation into clinical practice to assist clinicians in the difficult decision of whether to proceed with implantation. This study will be conducted in accordance with the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans (2014). We plan to publish the study results in a peer-reviewed full-length original article and present its findings at scientific conferences.

Trial registration number

NCT06138808.
Baseline tumour vessel perfusion as a non-invasive predictive biomarker for immune checkpoint therapy in non-small-cell lung cancer
Authors: Liu Zhenhua , Ma Ke , Jia Qingzhu , Yang Yunpeng , Fan Peng , Wang Ying , Wang Junhui , Sun Jiya , Sun Liansai , Shi Hongtai , Sun Liang , Zhu Bo , Xu Wei , Zhang Li , Jain Rakesh K. , Qin Songbing , Huang Yuhui
Published: August 2024

Objective

Current biomarkers for predicting immunotherapy response in non-small-cell lung cancer (NSCLC) are derived from invasive procedures with limited predictive accuracy. Thus, identifying a non-invasive predictive biomarker would improve patient stratification and precision immunotherapy.

Methods and analysis

In this retrospective multicohort study, the discovery cohort included 205 NSCLC patients screened from ORIENT-11 and an external validation (EV) cohort included 99 real-world NSCLC patients. The ‘onion-mode segmentation’ method was developed to extract ‘onion-mode perfusion’ (OMP) from contrast-enhanced CT images. The predictive performance of OMP or its combination with the PD-L1 Tumour Proportion Score (TPS) was evaluated by the area under the curve (AUC).

Results

High baseline OMP was associated with significantly longer survival and predicted patient response to combination anti-PD-(L)1 therapy in the discovery and EV cohorts. OMP complemented the PD-L1 TPS with superior predictive sensitivity (p=0.02). In the PD-L1 TPS<50% subgroup, OMP achieved an AUC of 0.77 for the estimation of treatment response (95% CI 0.66 to 0.86, p<0.0001). A simple bivariate model of OMP/PD-L1 robustly predicted therapeutic response in both the discovery (AUC 0.82, 95% CI 0.74 to 0.88, p<0.0001) and EV (AUC 0.80, 95% CI 0.67 to 0.89, p<0.0001) cohorts.

Conclusion

OMP, derived from routine CT examination, could serve as a non-invasive and cost-effective biomarker to predict NSCLC patient response to immune checkpoint inhibitor-based therapy. OMP could be used alone or in combination with other biomarkers to improve precision immunotherapy.
Barriers and facilitators when seeking healthcare for septic children in Ghana: a single-centre qualitative study of patient caregivers and emergency department clinicians
Authors: Denny Vanessa C. , Appiah John Adabie , Nadkarni Vinay M. , Dassah Ebenezer , Gyimah Mensah Ebenezer , Kwabena Adjei Timothy , Amisah Justicia , Nettey Gustav , Owusu Larko , Woods-Hill Charlotte Z. , Wolfe Heather A. , James Ebor Jacob G. , Ruhama Acheampong Princess
Published: August 2024

Background/purpose

Sepsis is a leading cause of morbidity, mortality and healthcare utilisation for children worldwide, particularly in resource-limited regions. In Kumasi, Ghana, organ system failure and mortality in children who present to the emergency department (ED) with symptoms of sepsis are often due to late presentation and lack of recognition and implementation of time-critical evidence-based interventions. The purpose of this study was to assess the barriers and facilitators for families in seeking healthcare for their septic children; and to understand the barriers and facilitators for ED providers in Kumasi to recognise and implement sepsis bundle interventions.

Design

Single-centre qualitative interviews of 39 caregivers and 35 ED providers in a teaching hospital in Kumasi, Ghana.

Results

Thematic analysis of data from caregivers about barriers included: fear of hospital, finances, transportation, delay from referring hospital, cultural/spiritual differences, limited autonomy and concerns with privacy and confidentiality. Negative impacts on family life included financial strain and neglect of other children. ED providers reported barriers included: lack of training, poor work environment and accessibility of equipment. Facilitators from caregivers and providers included some support from the National Health Insurance. Caregivers reported having positive experiences with frontline clinicians, which encouraged them to return to seek health services.

Implications

Qualitative structured interviews identified facilitator and critical barrier themes about seeking healthcare, and sepsis identification/management in the paediatric population arriving for care in our centre in Kumasi, Ghana. This study highlights significant deficiencies in healthcare systems that make sepsis management challenging in these settings.
Artificial intelligence applied to ‘omics data in liver disease: towards a personalised approach for diagnosis, prognosis and treatment
Authors: Ghosh Soumita , Zhao Xun , Alim Mouaid , Brudno Michael , Bhat Mamatha
Published: August 2024

Advancements in omics technologies and artificial intelligence (AI) methodologies are fuelling our progress towards personalised diagnosis, prognosis and treatment strategies in hepatology. This review provides a comprehensive overview of the current landscape of AI methods used for analysis of omics data in liver diseases. We present an overview of the prevalence of different omics levels across various liver diseases, as well as categorise the AI methodology used across the studies. Specifically, we highlight the predominance of transcriptomic and genomic profiling and the relatively sparse exploration of other levels such as the proteome and methylome, which represent untapped potential for novel insights. Publicly available database initiatives such as The Cancer Genome Atlas and The International Cancer Genome Consortium have paved the way for advancements in the diagnosis and treatment of hepatocellular carcinoma. However, the same availability of large omics datasets remains limited for other liver diseases. Furthermore, the application of sophisticated AI methods to handle the complexities of multiomics datasets requires substantial data to train and validate the models and faces challenges in achieving bias-free results with clinical utility. Strategies to address the paucity of data and capitalise on opportunities are discussed. Given the substantial global burden of chronic liver diseases, it is imperative that multicentre collaborations be established to generate large-scale omics data for early disease recognition and intervention. Exploring advanced AI methods is also necessary to maximise the potential of these datasets and improve early detection and personalised treatment strategies.
If Marc is Suzanne’s father, does it follow that Suzanne is Marc’s child? An experimental philosophy study in reproductive ethics
Authors: Hens Kristien , Moormann Emma , Smajdor Anna , Cutas Daniela
Published: August 2024

In this paper, we report the results from an experimental reproductive ethics study exploring questions about reproduction and parenthood. The main finding in our study is that, while we may assume that everyone understands these concepts and their relationship in the same way, this assumption may be unwarranted. For example, we may assume that if ‘x is y’s father’, it follows that ‘y is x’s child’. However, the participants in our study did not necessarily agree that it does follow. This means, at the very least, that we need to make sure all parties in a debate have the same relationships in mind when talking about reproduction and parenthood. Moreover, it gives us reason to explore more carefully the conditions which support or undermine the connections between these concepts. This cannot come from purely theoretical reasoning, nor from empirical research alone, but from the alliance between the two.
Advancing the practice of trauma: utilizing advanced practice providers to improve patient outcomes through a collaborative team approach
Authors: Lasinski Alaina M , Shaughnessy Allysen , Reynolds Benjamin , Forsythe Raquel , Kay Annika B , Yorkgitis Brian K , Younge Brandy N , Christmas Ashley B , Claridge Jeffrey A
Published: August 2024

Advanced practice providers (APPs) have become essential to trauma teams in the United States during the last few decades. The optimal utilization of APPs is not yet known and is likely highly variable secondary to many factors. We discuss three aspects of the multidisciplinary approach to caring for trauma patients. First, a review of the literature demonstrates that APPs in trauma improve quality of care, patient throughput, and decrease cost. We then report on models of APP utilization by comparing five trauma centers across the country, concluding that utilization remains highly variable due to several system and provider factors. The final portion of this review highlights current billing and coding practices in integrated teams considering recent changes to Centers for Medicare and Medicaid rules in 2024.
Role of genetics and the environment in the etiology of congenital diaphragmatichernia
Authors: Liu Siyuan , Yu Lan
Published: August 2024

Congenital diaphragmatic hernia (CDH) is a congenital malformation characterized by failure of diaphragm closure during embryonic development, leading to pulmonary hypoplasia and pulmonary hypertension, which contribute significantly to morbidity and mortality. The occurrence of CDH and pulmonary hypoplasia is theorized to result from both abnormalities in signaling pathways of smooth muscle cells in pleuroperitoneal folds and mechanical compression by abdominal organs within the chest cavity on the developing lungs. Although, the precise etiology of diaphragm maldevelopment in CDH is not fully understood, it is believed that interplay between genes and the environment contributes to its onset. Approximately 30% of patients with CDH possess chromosomal or single gene defects and these patients tend to have inferior outcomes compared with those without genetic associations. At present, approximately 150 gene variants have been linked to the occurrence of CDH. The variable expression of the CDH phenotype in the presence of a recognized genetic predisposition can be explained by an environmental effect on gene penetrance and expression. The retinoic acid pathway is thought to play an essential role in the interactions of genes and environment in CDH. However, apart from the gradually maturing retinol hypothesis, there is limited evidence implicating other environmental factors in CDH occurrence. This review aims to describe the pathogenesis of CDH by summarizing the genetic defects and potential environmental influences on CDH development.
Incorporating region-variability of model bias into liquefaction-triggering procedures for sandy and gravelly soils through BUS-powered hierarchical Bayesian updating
Authors: Wang Mao-Xin , Leung Y.F. , Lo M.K.
Published: August 2024

The accuracy of cyclic stress-based liquefaction-triggering assessment procedures can vary systematically from region to region, but it is challenging to regionalize models due to the lack of region-specific data. This paper presents a hierarchical Bayesian modeling (HBM)-based framework for incorporation of inter-region and intra-region variabilities of the bias factor in liquefaction-triggering procedures. A key feature is that the BUS approach (Bayesian Updating with Structural reliability methods) is combined with subset simulation to efficiently update high-dimensional statistics of bias factors. Another feature is a new four-hyperparameter HBM considering both region-specific means and variances of bias factors. This framework is utilized to develop three sets of region-specific liquefaction probability models for practical applications, covering liquefaction-susceptible sandy and gravelly soils. The results show that the four-hyperparameter HBM generally matches better with liquefaction observations and produces larger total variance, compared to the lumped-region modeling and the HBM with only region-specific means. Meanwhile, the population-level distribution and the weighting factor of liquefaction/non-liquefaction occurrence can considerably affect model performance. Furthermore, a discrete integration-based probabilistic method is suggested for liquefaction-triggering hazard assessment. Illustrative examples indicate that different HBM configurations can yield notably different liquefaction hazard results while neglecting the region-variability tends to be unconservative.
Can operational tactics compensate for weaker tensile properties of biodegradable gillnets?
Authors: Savina Esther , Bertelsen Ida Maria Gieysztor , Cerbule Kristine , Gué Louis Le , Herrmann Bent , Krag Ludvig A.
Published: August 2024

This study aimed at discriminating between the effects of physical strain due to the interactive effect of gear operation and degradation, and degradation only, on the differences in breaking strength, strain, and stiffness at break of polybutylene succinate-co-adipate-co-terephthalate (PBSAT) (biodegradable) and PA6 (nylon) gillnet materials, and to compare the effect of fish species and resulting capture mode on catch efficiency for a roundfish species, Atlantic cod ( Gadus morhua), and a flatfish species, European plaice ( Pleuronectes platessa) in the Danish coastal gillnet fishery. The PBSAT meshes were much weaker than PA6 already at the start of the experiment. There were 58% (95% Confidence Interval (CI): 38%–79%) less cod and 32% (CI: 17%–49%) less plaice after 4 months in the PBSAT gillnets. We did not observe significant differences between the interactive effect of gear operation and degradation, and degradation only, and in capture modes. We conclude that reduction in catch efficiency results from a combination of weaker mechanical properties worsened by degradation during, e.g., transport and storage, and a species given shape and swimming ability.
Revised historic harvest data improve estimates of the impacts of human activities on reported greenhouse gas emissions and removals in Canada’s managed forest
Authors: Kurz W.A. , Hudson B. , Neilson E.T. , Fellows M. , Hafer M. , MacDonald J.D.
Published: August 2024

Guidelines for international reporting of greenhouse gas emissions and removals in the forest sector require a land-based approach that includes all lands subject to forest management activities such as harvest, forest inventory, regeneration, management of natural disturbances, and protected areas. The reported net greenhouse gas balance of managed forests is not limited to forest stands resulting from timber harvest and wood product use. Reporting guidelines specify methods to reduce interannual variability in reported emissions attributable to natural disturbances. In Canada, the initial (1990) assignment of all inventoried stands to anthropogenic or natural disturbance reporting categories is determined by the last stand-initiating disturbance. A new compilation of historic (1889 to 1989) harvest data in Canada reduces the area reported in the anthropogenic category by 34 million hectares (20%) in 1990. This area transfer from anthropogenic to natural origin reduces the carbon sink reported as anthropogenic by 113 Mt CO2e yr−1 (56%) in 1990 and by 30 Mt CO2e yr−1 (23%) in 2021.
Exact dynamical black hole solutions in five or higher dimensions
Authors: Fahim Bardia H. , Ghezelbash A. M.
Published: August 2024

We construct new classes of the dynamical black hole solutions in five or higher dimensional Einstein–Maxwell theory, coupled to a dilaton field, in the presence of an arbitrary cosmological constant. The dilaton field interacts non-trivially with the Maxwell field, as well as the cosmological constant, with two arbitrary coupling constants. The solutions are non-stationary, and almost conformally regular everywhere. To construct the solutions, we use the four-dimensional Bianchi type IX geometry, as the base space. We find three different classes of solutions, based on the values of the coupling constants. We notice that our solutions could be asymptotically de-Sitter, anti-de-Sitter or flat. We find the relevant quantities of the solutions, and discuss the properties of the solutions.
Complete de-wetting of lipid membranes on silicon carbide
Authors: Ryskulov Ruslan , Pedrueza-Villalmanzo Esteban , Tatli Yagiz Alp , Gözen Irep , Jesorka Aldo
Published: August 2024

We report temperature-induced complete de-wetting of phospholipid membranes from thermally evaporated silicon carbide (SiC) substrates, which occurs in the form of fractal patterns. Excess membrane material released as a result of de-wetting, transforms into fluid-filled membrane pockets, or leads to vesicle formation. The membrane pockets are composed of a double lipid membrane. These double bilayer superstructures, i.e. isolated membrane-enclosed fluid volumes, bring the internal contents into direct contact with the surface. This membrane morphology can be viewed as an alternative prebiotic assembly mechanism with possible implications for protocell development, where physicochemical surface interactions with internal primitive cell contents are greatly facilitated.
Discriminative Feature Learning Through Angular Margin-Based Softmax Losses for Breast Cancer Classification
Authors: Alirezazadeh Pendar , Dornaika Fadi , Moujahid Abdelmalik
Published: August 2024

When many histopathological breast images with different magnification levels need to be analyzed, diagnosing benign or malignant cancer from the images can be time-consuming. Automatic classification of histopathological images of breast cancer can support the diagnostic workflow in pathology, reducing analysis time. Recently, convolutional neural networks (CNNs) have been used for more accurate classification of breast cancer histopathological images. CNNs typically highlight semantic information to extract discriminative features. However, the traditional softmax loss used by CNNs usually lacks sufficient discriminative power. To address this problem, several angular margin-based softmax loss functions have been proposed, including Large Margin Softmax Loss (A-Softmax), Large Margin Cosine Loss (CosFace), Additive Angular Margin Loss (ArcFace), and Linear ArcFace (Li-ArcFace). All of these improved losses are based on the same concept: maximizing inter-class variance while minimizing intra-class distance. This paper focuses on these four losses and their effectiveness in extracting discriminative features and creating decision margins between classes. Extensive experimental evaluations were conducted on a public and well-known histopathological breast cancer image dataset (BreakHis). Further experiments with the BACH dataset for breast cancer classification and the SARS-CoV-2 CT-scan dataset for COVID-19 detection affirm the generalization capability of angular margin-based softmax losses in medical image classification.
Current-controlled sedimentation in a megatransform system: a case study of the Charlie–Gibbs Fracture Zone
Authors: Dorokhova Evgenia V. , Sokolov Sergey Y. , Ponomarenko Ekaterina P. , Bashirova Leyla D. , Pugacheva Tatiana L. , Urazmuratova Zarina F. , Laskina Daria N. , Dobrolyubova Kseniya O.
Published: August 2024

The Charlie–Gibbs Fracture Zone is the main transform system in the North Atlantic Ocean. It serves as a primary deep-water gateway for the Iceland–Scotland Overflow Water current. Using high-resolution seismo-acoustic profiling, three types of contourite drift were identified in the valleys of the inactive fractures and active transform of the Charlie–Gibbs Fracture Zone: (1) channel-related drifts; (2) confined drift; and (3) plastered drift. The Iceland–Scotland Overflow Water current is the main agent controlling drift formation in the northern valley and eastern part of the southern valley, while it is suggested that the Denmark Strait Overflow Water or Lower Deep Water dominate in the western part of the southern valley. Examination of two sediment cores shows that the contourite drifts at least at their upper parts consist of alternating muddy and silty contourites and pelagic/hemipelagic sediments. The contourite deposition corresponds to the present interglacial interval. Pelagic/hemipelagic sedimentation prevailed during a glacial interval (marine isotope stages 3–2) and the last glacial/interglacial transition, corresponding with high ice-rafted debris input. The position of the highly productive Subarctic Front over the study area induced the formation of diatom ooze beds at the beginning of marine isotope stage 1 and high-carbonate pelagites during some intervals of marine isotope stage 3.
RecenTo: Finding Top-K Flows of the Recent Past
Authors: Ozery Aviya , Diamant Jonathan , Landau Feibish Shir
Published: August 2024

Recent advances in programmable networks enable network operators to perform fine-grained analysis on all of the traffic as it traverses the network. One of the most common tasks, that has been widely studied, is to find the heavy hitter flows or the top-k flows. Several solutions have been presented that find such flows using a constant amount of memory and working within the confined resources and capabilities of the data plane. However, in order to pinpoint critical issues in the network, it is necessary to detect the flows that have been heavy in the recent past. Yet, existing approaches perform the task of heavy flow detection continuously, such that they can find the heavy flows over a boundless time period. In order to find heavy flows for shorter time intervals, sliding windows are often used. This requires multiple instances of the structure to clean out old data while still recording new data. Thus this requires a large amount of resources, and also requires predetermining the fixed length of the windows. We provide a formal definition of the recent top-K flows on a given stream, and present RecenTo a new deterministic counter-based algorithm for finding such flows in the data plane. The innovative technique used in RecenTo enables it to 'self-clean', thus making it easier for newer flows to enter the structure. RecenTo also makes use of a novel structure for maintaining the key and counter of the flows that provides support for the
mutual dependence
between them (i.e., sometimes the count is changed based on key and sometimes vice-versa). We evaluate RecenTo over continuous chunks of traffic and show that it consistently achieves a recall rate of ~ 0.9 for finding the top-k flows in each chunk.
Addressing Uncertainty in Biodesign through Digital Twins: A Case of Biofabrication with Mycelium
Authors: Vu Đan Vy , Funk Mathias , Huang Yi-Ching (Janet) , Barati Bahareh
Published: August 2024

New digital tools offer biodesign with unprecedented opportunities for monitoring, fabricating, iterating, and scaling designs. Serving aligned purposes and beyond, the Digital Twin (DT) is an emerging concept in bioindustries including bioprocessing and agri-food. In these fields, DTs enable comprehensive digital representations of a living system or process with continuous bidirectional connection to the physical world. Despite the concept’s potential to address certain challenges of uncertainty in designing (with) living systems, its applications and implications in biodesign and research remain largely underexplored. To bridge this gap, we propose a conceptual framework that synthesizes existing instantiations of DTs within bioindustries through a dataflow lens. We mobilize the framework through a proof-of-concept DT for biofabrication with mycelium, by unpacking the dataflows within the identified design and operation cycles. We conclude with a discussion on how DT capabilities respond to uncertainties in designing with living systems, limitations, and future work.
Efficient Low-Memory Implementation of Sparse CNNs Using Encoded Partitioned Hybrid Sparse Format
Authors: Basak Barnali , Dasgupta Pallab , Pal Arpan
Published: August 2024

Certain data compression techniques like pruning leads to
unstructured sparse Convolution Neural Network (CNN)
models without directly leveraging sparsity in optimizing both memory consumption and inference latency of a model having low to medium sparsity. State-of-the-art storage techniques either optimize model size at the cost of execution latency or optimize inference latency at the overhead of the memory consumption of the model. This tradeoff is largely due to the absence of storage selection methodology addressing
sparsity sensitivity
, arising from varied
sparsity
and positions of nonzero values called
sparsity structure
across different sparse layers of a model. However, this issue remains unexplored due to the lack of support to handle sparse data in the current deployment standards for edge devices.

This article introduces a data compaction strategy for
unstructured
sparse data that
not only compresses nonzero data but also encodes it, leveraging the memory consumption and latency reduction benefits of both data compression and data encoding techniques
. We propose a novel storage representation, named
Encoded Partitioned Hybrid Sparse
(EPaHS) format, which addresses sparsity sensitivity by customizing data storage based on the sparsity structure of the data. Our data compaction technique and storage solution optimizes the tradeoff between the memory consumption and inference latency of a sparse model without altering the network architecture and affecting its accuracy. Our solution easily extends to higher-dimensional data and outperforms standard storage solutions. It proves to be beneficial to all the valid mode orientations of multi-dimensional data.

For an important health and wellness application, a single-lead short-time ECG classification model, EPaHS achieves up to

\({\tt 16.18\%}\)

reduction in size and

\({\tt 15.16\%}\)

reduction in latency when compared to its original model of

\({\tt 42}\)

MB size and

\({\tt 26.35}\)

sec latency, having

\({\tt \approx 59\%}\)

sparsity. For a ResNet50 model handling higher-dimensional data, it achieves

\({\tt 21.33\%}\)

size reduction and

\({\tt 53.9\%}\)

latency gain against the original model of

\({\tt 3265}\)

KB size and

\({\tt 1.7}\)

sec latency, having

\({\tt \approx 67\%}\)

sparsity.
Algorithm 1046: An Improved Recurrence Method for the Scaled Complex Error Function
Authors: Thompson Ian
Published: August 2024

Calculation of the scaled complex error function

\(w(z)\)

by recurrence is discussed, and a new method for determining the number of steps required to achieve a given accuracy is introduced. This method is found to work throughout the complex plane, except for a short section of the real line, centred at the origin. An algorithm based on this analysis is implemented; Taylor series with stored coefficients are used to compute

\(w(z)\)

in a small region where recurrence is not efficient. The new algorithm is tested extensively and found to outperform earlier recurrence-based codes. It also performs favourably against recent codes based on other methods.
Empirical Study of Impact of Solidity Compiler Updates on Vulnerabilities in Ethereum Smart Contracts
Authors: Kado Chihiro , Yanai Naoto , Cruz Jason Paul , Yamashita Kyosuke , Okamura Shingo
Published: August 2024

Vulnerabilities in Ethereum smart contracts often cause significant financial damage. Whereas the Solidity compiler has been updated to mitigate vulnerabilities, the effectiveness of these updates remains undisclosed to the best of our knowledge. In this paper, we aim to shed light on the impact of compiler versions on reducing vulnerabilities in Ethereum smart contracts. To achieve this, we collected 497,344 contracts with Solidity source codes from the Ethereum blockchain and analyzed their vulnerabilities. For three vulnerabilities of high severity, i.e.,
Locked Money
,
Using tx.origin
, and
Unchecked Call
, we illustrate their appearance rate changes, showing decreases attributed to major updates of the Solidity compiler. Subsequently, we found the following four key insights. Firstly, updates to version 0.6 and version 0.8 led to decreased appearance rates for
Locked Money
. Secondly, regardless of compiler updates, the appearance rate for
Using tx.origin
was significantly low. Thirdly, the appearance rate for
Unchecked Call
significantly decreased from version 0.5 to version 0.8. Lastly, as an incidental discovery from our empirical study, we identified implications for code clones, which merit attention from subsequent researchers and developers.
A Robust Newton Iteration Method for Mixed-Cell-Height Circuit Legalization Under Technology and Region Constraints
Authors: Zhou Chencan , Cao Yang , Shi Quan , Wang Luxin , Wen Xiaoqing
Published: August 2024

The evolution of advanced technology nodes has prompted a shift toward mixed-cell-height circuit design, while the introduction of technology and fence region constraints further increases the complexity of placement. In this article, we innovatively transform the mixed-cell-height circuit legalization problem into a generalized absolute value equation (GAVE) and propose a novel and effective robust Newton (RN) iteration method to address the challenge of the legalization problem.

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First, the window-based cell insertion technique is applied to obtain the initial cell row allocation and cell order, and the cells are allocated to the matching region based on the R-tree structure. Then, the legalization problem of cells within the region is transformed into a GAVE, and an RN iteration method is proposed to solve the GAVE. Finally, the maximum displacement cells and technology violation cells are optimized based on a greedy method. Experimental results confirm the efficiency and robustness of the proposed method compared with the state-of-the-art methods.
Revolutionizing Visuals: The Role of Generative AI in Modern Image Generation
Authors: Bansal Gaurang , Nawal Aditya , Chamola Vinay , Herencsar Norbert
Published: August 2024

Traditional multimedia experiences are undergoing a transformation as generative AI integration fosters enhanced creative workflows, streamlines content creation processes, and unlocks the potential for entirely new forms of multimedia storytelling. It has potential to generate captivating visuals to accompany a documentary based solely on historical text descriptions, or creating personalized and interactive multimedia experiences tailored to individual user preferences. From the high-resolution cameras in our smartphones to the immersive experiences offered by the latest technologies, the impact of generative imaging undeniable. This study delves into the burgeoning field of generative AI, with a focus on its revolutionary impact on image generation. It explores the background of traditional imaging in consumer electronics and the motivations for integrating AI, leading to enhanced capabilities in various applications. The research critically examines current advancements in state-of-the-art technologies like DALL-E 2, Craiyon, Stable Diffusion, Imagen, Jasper, NightCafe, and Deep AI, assessing their performance on parameters such as image quality, diversity, and efficiency. It also addresses the limitations and ethical challenges posed by this integration, balancing creative autonomy with AI automation. The novelty of this work lies in its comprehensive analysis and comparison of these AI systems, providing insightful results that highlight both their strengths and areas for improvement. The conclusion underscores the transformative potential of generative AI in image generation, paving the way for future research and development to further enhance and refine these technologies. This article serves as a critical guide for understanding the current landscape and future prospects of AI-driven image creation, offering a glimpse into the evolving synergy between human creativity and artificial intelligence.
Reimagining Online Education: Breaking down colonial barriers to learning
Authors: Samuel Anita
Published: August 2024

eLearning, while seemingly democratizing education, carries colonial biases in curriculum, language, and technology. Decolonization requires recognizing these constraints, disrupting the status quo, and embracing alternatives. Strategies include decentering Western voices, co-creating learning experiences, challenging linguistic hegemony, bridging the digital divide, and leveraging technology for decolonization. This ongoing process fosters inclusive and equitable education by acknowledging the colonial legacy and actively dismantling it.
Remaining Useful Life Prediction of Lithium-Ion Batteries Based on Simplified Electrochemical Model and TSO-TCN
Authors: Lin Chen , Yang Dongjiang , Zhou Zhongkai
Published: August 2024

Accurate prediction of the remaining useful life (RUL) of lithium-ion battery is critical in practical applications, but is challenging due to the presence of multiple aging pathways and nonlinear degradation mechanisms. In this paper, a method for RUL prediction is proposed combined with battery capacity aging mechanism based on transient search optimization (TSO)-temporal convolutional network (TCN) algorithm. First, the particle swarm optimization algorithm is used to derive three health indicators directly related to capacity loss from a simplified electrochemical model. Then, the TCN parameters are optimized with transient search algorithm to obtain the optimal prediction model. Finally, the RUL prediction are compared with other typical algorithms, and the results show that the proposed method can accurately predict the RUL of lithium-ion battery, and the life prediction error is within 10 cycles. Compared to TCN, the prediction results remain accurate even with less training data, and the error metrics are reduced by about 50% with the maximum error only 7 cycles from the 250th charge/discharge cycle.
Bi-Doped P2 layered Sodium-Ion Battery Cathode with Improved Cycling Stability
Authors: Wu Xinsheng , Whitacre Jay F.
Published: August 2024

P2-phased layered oxide materials have been extensively studied as cathode material for sodium-ion batteries due to their high capacities and ionic conductivities, making them promising for large-scale applications. Additionally, manganese-based compounds, with their low cost and high capacity, have attracted significant attention in recent years. However, challenges remain regarding durability issues and related structural instability caused by the Jahn-Teller effect induced by Mn3+ ions formed during the cycling process in these materials, which causes manganese dissolution during use. In this study, we introduce a cathode composition of Na0.8Mn0.75Fe0.2Al0.05O2 and show that bismuth doping enhances the structural stability of the cathode material during electrochemical cycling. Electrodes with varying levels of bismuth doping were compared in half-cell configurations; material with 1% bismuth doping demonstrated outstanding stability, retaining 95.8% capacity after 200 cycles at a 0.2 C rate through the full potential range. dQ/dV analysis shows that bismuth doping effectively suppresses the excess Mn redox, which could otherwise deteriorate the cathode structure. As a proof of concept, Bi-doped materials were implemented in full cells paired with hard carbon that exhibited much better stability than those without bismuth doping. Lastly, the moisture and air stability of the bismuth-doped electrode were tested, demonstrating good stability.
A Bifunctional Carbon-LiNO3 Composite Interlayer for Stable Lithium Metal Powder Electrodes as High Energy Density Anode Material in Lithium Batteries
Authors: Mpupuni Carlos Tafara , Mukhan Orynbassar , Yun Ji-Su , Kim Sung-Soo
Published: August 2024

Lithium metal remains a promising candidate for high-energy-density rechargeable batteries due to its exceptional specific capacity and low reduction potential. However, practical implementation of lithium metal anodes faces challenges such as dendrite formation, limited cycle life, and safety concerns. This study introduces a novel approach to enhance the performance of lithium metal powder (LMP)-based electrodes by embedding a LiNO3-carbon composite interlayer between the LMP electrode and the copper foil current collector. The N-rich carbon interlayer acts as a reservoir for LiNO3, enabling its gradual release to maintain prolonged stability of the interfacial reactions of the Li-metal and providing additional Li nucleation sites. Our findings demonstrate that the LiNO3-carbon composite effectively suppresses dendrite formation, improves reversible capacity, and stabilizes the solid electrolyte interphase. Additionally, we validated the fast-charging capabilities of the Li/NCM622 half-cell employing the LiNO3-carbon-coated Cu foil with LMP electrodes. Our results highlight the significant synergistic effect of the LiNO3 additive and carbon interlayer in enhancing the performance of lithium metal-based batteries.
A Comparative Study of Nano and Micro-Sized Silicon in Lithium-Ion Cells with a Nickel-Rich Cathode
Authors: Zhang Sheng S.
Published: August 2024

Reducing particle size has been widely adopted to mitigate the cracking and pulverization of silicon particles and to enhance electrode reaction kinetics for silicon electrodes in cycling. However, the increased surface area promotes parasitic reactions with electrolyte solvents. This work comparatively studies nano-sized silicon (Si-NP) and micro-sized silicon (Si-MP) as anodes in Li-ion cells using nickel-rich LiNi0.80Co0.1Mn0.1O2 (NCM811) as the cathode. The focus is on capacity, capacity retention, Coulombic efficiency (CE), and rate capability by changing the negative-to-positive capacity (N/P) ratio and charging cutoff voltage. It is found that Si-NP initially exhibits a CE above 90%, however, it rarely exceeds 98% in subsequent cycles, leading to rapid capacity fade. Additionally, increasing the N/P ratio and lowering the charging cutoff voltage does not obviously improve the cycling stability of Si-NP cells. Compared with Si-NP, Si-MP experiences lower capacity and lower CE in the initial several cycles. However, with continued cycling, both the capacity and CE gradually increase to a maximum and stably remain at ∼99.9%. The findings of this work suggest that, with its excellent rate capability, Si-MP may be more advantageous than Si-NP in developing practical Li-ion batteries, provided its low CE during initial cycles can be successfully addressed.