bluuebunny/crossref_metadata_2025 huggingface dataset:
Reducing uncertainty of high-latitude ecosystem models through identification of key parameters
Authors: Mevenkamp Hannah , Wunderling Nico , Bhatt Uma , Carman Tobey , Friedemann Donges Jonathan , Genet Helene , Serbin Shawn , Winkelmann Ricarda , Susanne Euskirchen Eugenie
Published: August 2023

Climate change is having significant impacts on Earth’s ecosystems and carbon budgets, and in the Arctic may drive a shift from an historic carbon sink to a source. Large uncertainties in terrestrial biosphere models (TBMs) used to forecast Arctic changes demonstrate the challenges of determining the timing and extent of this possible switch. This spread in model predictions can limit the ability of TBMs to guide management and policy decisions. One of the most influential sources of model uncertainty is model parameterization. Parameter uncertainty results in part from a mismatch between available data in databases and model needs. We identify that mismatch for three TBMs, DVM-DOS-TEM, SIPNET and ED2, and four databases with information on Arctic and boreal above- and belowground traits that may be applied to model parametrization. However, focusing solely on such data gaps can introduce biases towards simple models and ignores structural model uncertainty, another main source for model uncertainty. Therefore, we develop a causal loop diagram (CLD) of the Arctic and boreal ecosystem that includes unquantified, and thus unmodeled, processes. We map model parameters to processes in the CLD and assess parameter vulnerability via the internal network structure. One important substructure, feed forward loops (FFLs), describe processes that are linked both directly and indirectly. When the model parameters are data-informed, these indirect processes might be implicitly included in the model, but if not, they have the potential to introduce significant model uncertainty. We find that the parameters describing the impact of local temperature on microbial activity are associated with a particularly high number of FFLs but are not constrained well by existing data. By employing ecological models of varying complexity, databases, and network methods, we identify the key parameters responsible for limited model accuracy. They should be prioritized for future data sampling to reduce model uncertainty.
Regional implications of carbon dioxide removal in meeting net zero targets for the United States
Authors: Fauvel Chloé , Fuhrman Jay , Ou Yang , Shobe William , Doney Scott , McJeon Haewon , Clarens Andrés
Published: August 2023

Abstract

Net-zero greenhouse gas emission targets are central to current international efforts to stabilize global climate, and many of these plans rely on carbon dioxide removal (CDR) to meet mid-century goals. CDR can be performed via nature-based approaches, such as afforestation, or engineered approaches, such as direct air capture. Both will have large impacts in the regions where they are sited. We used the Global Change Analysis Model for the United States to analyze how regional resources will influence and be influenced by CDR deployment in service of United States national net-zero targets. Our modeling suggests that CDR will be deployed extensively, but unevenly, across the country. A number of US states have the resources, such as geologic carbon storage capacity and agricultural land, needed to become net exporters of negative emissions. But this will require reallocation of resources, such as natural gas and electricity, and dramatically increase water and fertilizer use in many places. Modeling these kinds of regional or sub-national impacts associated with CDR, as intrinsically uncertain as it is at this time, is critical for understanding its true potential in meeting decarbonization commitments.
Analysis of yield and types of carrageenan from different strains at Kupang Bay seaweed production center, East Nusa Tenggara
Authors: Sani C S , Oedjoe M D R , Turupadang W
Published: August 2023

Kappaphycus alvarezzi is a species widely cultivated by the seaweed farmers surrounding Kupang Bay since the early 2000s. K. alvarezzi is sold as raw materials for the carrageenan industry as its hydrocolloid properties are used as emulsion and suspension stabilizers in the food and pharmaceutical industries. This study determines the yield and identifies the type of carrageenan from algal farms at Kupang Bay. Samples are collected from five production centers, then extracted at the Wet Laboratory at the Undana Faculty of Animal Husbandry, Marine and Fisheries in Kupang; and the extracted carrageenan is then analyzed using infrared spectroscopy at the Laboratory of the Faculty of Advanced and Multidisciplinary Technology Universitas Airlangga in Surabaya. The results showed that the highest yield of carrageenan was seaweed from Sulamu (25.72%) then, followed by Oenaek (19.6%), Tablolong A (13.48%), South Semau (11%), and Tablolong B as the lowest yield (9.6% ). Both the presence of functional groups such as D-galactose-4-sulphate and 3,6 anhydro D-galactose groups and the absence of D-galactose-2-sulfate and the 3,6 anhydrogalactose-2-sulfate group, concluded that the type of carrageenan produced in Kupang Bay is the kappa carrageenan.
Population status of the oriental pied hornbill in oil palm landscapes with a conserved natural habitat in Runtu Village, West Kotawaringin, Central Kalimantan
Authors: Yusran A , Mulyani Y A , Kartono A P , Ramadhan G F , Sugeng W M H , Sahari B
Published: August 2023

Oriental Pied Hornbill is a member of the Bucerotidae family that can use rather changing habitats, including a forest fragment in Runtu, Central Kalimantan. The objective of this study is to evaluate the population status of Anthracoceros albirostris in an oil palm concession with a conserved natural habitat at Runtu, Kotawaringin Barat, Central Kalimantan. Habitat profiling for oriental pied hornbill is important to understand its role in supporting the population growth and sustainability of oriental pied hornbill in the area in question. The method to measure the size of the oriental pied hornbill’s population was a strip transect, and the habitat profile was evaluated using a combination of single plot methods. In total, there are 35 plant species belonging to seven families which serve as sources of food for hornbills identified to occur in the study area. The research shows that the oriental pied hornbill frequently and consistently visits Ficus variegata, F. aurata, F benjamina, Polyalthia xanthopetala, and Baccaurea bracteata during the observation period. The appearance of the oriental pied hornbill was found to be higher in the morning than the afternoon, with 4.37 ± 2.729 and 4.68 ± 6.03 individuals respectively. This study also found that the male and female ratio was 3: 4 with clustered dispersal patterns.
Wildlife complexity in four habitat types in oil palm landscape, Daha Barat, South Kalimantan
Authors: Kurniawan H , Yusran ‘A , Ramadhan G F , Wahyudiyono H S , Sahari B
Published: August 2023

Oil palm concessions generally posses different types habitats, such as riparian or patches of natural vegetation that can be a home for many wildlife species. This study aims to evaluate the complexity of wildlife species inhabiting oil palm concession containing various types habitats in Daha Barat, South Kalimantan. The study was conducted between June 2019 and September 2020. In addition to oil palm, this research also identified Galam (Melaleuca leucadendron), Mahang (Macaranga sp), swamp bushes, and Purun (Lepironia articulata) that were commonly found in the study area. The study has identified 10 species of mammals, 84 species of birds, 6 species of amphibians, and 18 species of reptiles inhabiting the study area. The highest species richness of wildlife was identifi to occur in the swamp bush habitat (91 species), followed by the Galam forest habitat (90 species), macaranga forest habitat (78 species), and oil palm habitat (75 species). However, some species are identified to occur across habitat types, and some others are only in one or two habitat types. Insectivorous and piscivorous birds are commonly found in the study area. The existence of various types of vegetation is expected to support a higher amount of both individuals and species of wildlife inhabiting the study area.
Citizen science reveal new distribution record and possibility of herpetofauna alien species spread in Java – Bali Region
Authors: Maharani N , Kusrini M D , Hamidy A
Published: August 2023

In Indonesia, several reports have been related to the distribution of alien herpetofauna species, especially in Java-Bali. This research aims to reveal the distribution record and possible new distribution of herpetofauna species in the Java-Bali region, including the possibility of alien species. Amfibi Reptil Kita (ARK) uses citizen science methods to collect herpetofauna data from 2017 – 2020 to see possible distribution of herpetofauna new species in the Java – Bali region. The data are then separated by year and region for analysis. After sorting, the data matched the distribution of species through various libraries and geotagged references based on each account. There are six new species recorded in Java-Bali referred to alien species. There are six new species recorded in Java-Bali reffered to alien species. Polypedates macrotis is a new record for Java, while two other amphibian species, Ranoidea caerulea and Lithobates catesbeianus are species whose natural distribution is not in Java-Bali. For reptiles, three types are indicated as alien species in Java-Bali, namely Calotes versicolor, Lamprolepis smaragdina and Pelodiscus sinensis. If alien species such as Lithobates catesbeianus, Calotes versicolor and Lamprolepis smaragdina are not managed properly there are possibility of becoming invasive species and threatening the existence of local species.
Macaque–Human Interaction and the Societal Perceptions of Macaques in Kalisalak Forest, Central Java–Indonesia
Authors: Imtiyaaz C D , Wahyudiana N H , Nasution E K , Puspitasari I G A A R , Al-Hakim R R
Published: August 2023

The 2030 agenda for sustainable development, with its 17 Sustainable Development Goals (SDGs), aims to meet people’s and nature’s needs. Macaque–Human Interaction (MHI) is connected between SDGs 15: Biodiversity and SDGs 3: Good health and well-being, that biodiversity and conservation are crucial to ensure healthy lives and promote well-being for people. Kalisalak Forest is one of the habitats of a long-tailed macaque on Java Island that is also commonly used as a grand forest park for multiple visitation purposes. This species is now listed as endangered by IUCN Red List. The MHI is found on this site but has never been studied. This research conducted a quantitative approach that emphasizes the respondent experience of visitors by the Lemeshow formula with the survey technique and ad-libitum sampling method. Our results show that the interaction initiated by macaques tends to be affiliative, feeding from human food provisioned. Visitor dominants are local people, which are already accustomed to the presence of the macaques, so it may cause the interaction to be neutral. Besides, humans initiate macaques and tend to be neutral, walking. Macaques in this site were habituated to human presence, familiar, and attracted to provisioned food. In addition, this condition can probably influence zoonotic disease. In that respect, minimizing the disturbance of natural systems would significantly help prevent the emergence and spread of new pathogens causing such zoonotic diseases. Our recommendations need more emphasis on forest management to avoid the potential zoonotic disease based on that MHI.
Mapping of land use change using Sentinel-2 Multi Spectral Instrument (MSI) imagery and Google Earth Engine mapping platform at Dramaga, Bogor Regency, Indonesia
Authors: Rahmawati A D , Asy’Ari R , Ranti A , Prameswari F A , Ameiliani T H , Khairunnisa Z N
Published: August 2023

Dramaga District is an urban buffer area in Jabodetabek Metropolitan Megacity and has various types of land use. The land crisis due to population growth in urban areas has implications for the surrounding buffer areas, so land use changes often occur. Mapping of land use change in the period 2017 to 2021 carried out area is a response to the impact of urban activities and the need for fast and accurate. The mapping platform, Google Earth Engine based on cloud computing, was involved in this research. The land use classification process from Sentinel-2 MultiSpectral (MSI) imagery uses the Random Forest (RF) machine learning algorithm classification method and is assisted by several types of indexes such as vegetation index (NDVI, SLAVI, ARVI, SAVI, and EVI), water index (NDWI, MNDWI, and LSWI), and building index (IBI and NDBI). This study shows that there are changes in several types of land use such as forests, agriculture, built-up areas, plantations, and water bodies. The classification of land use accuracy level reaches 86.00% (Overall Accuracy) and 0.82 (Kappa Statistics) so that this spatial information can be used as consideration for policy makers to determine the allocation and utilization of spatial planning.
Oil-palm village vs non-oil palm village: lesson learned from a mix method study involving village development index
Authors: Oktarina S D , Nasdian F T , Nurkhoiry R , Aulia R U , Sipayung T
Published: August 2023

Indonesia has acknowledged the oil palm industry as a blessing in disguise. Despite being most critically discussed commodity, it has generated considerable benefits not only economically and socially, but also ecologically for the archipelago. Many debates have gone against it. That evidence had been investigated at the micro-scale level or individual farm level spot by spot, but only a few have been discussed in a nationally representative manner. Many had also claimed that palm oil might spill over to farm individual prosperity, reducing deprivation and even promoting structural transformation in the ground. However, not much has been evaluated to what extent the improvement process is transferred at the village level, as the most immediate administrative level governs the oil palm farmers. Thus, this work is aimed to evaluate the impact of oil palm adopting-villages compared to that of the non-oil palm adopting-villages in terms of its village development index (IDM, Indeks Desa Membangun). The study uses mix-method analysis, which combines propensity score matching (PSM) to assess the impact quantitatively, and text mining analysis to confirm the former result qualitatively. The process is supplied with village characteristics from the eight most prominent oil palm-producing provinces, such as Riau, North Sumatra, West Kalimantan, Central Kalimantan, East Kalimantan, South Sumatra, Jambi, and Aceh. The result indicated that oil palm plantation has emerging benevolent outcomes in terms of economic, social, and ecology aspects at the village level. Yet, it is revealed that some issues remained questioned
Land use allocation based on multi-goal linear programming model: a case study of Central Luzon State University
Authors: Abella G P L , Ramos E E , Tubay J M , Fiegalan F T
Published: August 2023

Allocating and reallocating land resources is critical to a long-term land use planning and is a key component to achieve a balanced land use system. This provides appropriate space for varied land uses while preserving the environment for future generations. It is found to be an excellent measure for development and sustainability of an area. Using multiple goal linear programming as a decision support system, this study highlighted the optimization of land use allocation at Central Luzon State University to meet the needs for sustainable development. All the seven (7) general land use classifications determined in the University: agricultural, institutional, residential, commercial, fisheries (pond/fish tanks), roads and open areas were assessed in crafting the Land Use Development and Infrastructure Plan (LUDIP) for 2021 to 2031. The findings demonstrated that the priority goals set by the CLSU constituents: (1) minimizing disaster risk, (2) maximizing land suitability, (3) maximizing research capability, maximizing social development, and maximizing economic value were achieved with the aid of Gurobi. Agricultural and commercial growth, residential, social, and infrastructure development for all constituents, research development, climate change adaptation, and cultural heritage preservation were all aided by the land use optimization in the LUDIP.
Cost-benefit analysis framework for utility-scale solar energy development: a life cycle approach
Authors: Asirin  , Siregar H , Juanda B , Indraprahasta G S
Published: August 2023

One of the policy options for sustainable urban and regional development is the development of renewable energy by developing utility-scale solar energy. The development of utility-scale solar energy contributes to the improvement of social welfare such as the production of electrical energy and the reduction of greenhouse gas emissions. On the other hand, the development of utility-scale solar energy can have a negative impact such as natural landscape change and solid waste. The cost-benefit analysis method can be used to analyze whether the development of utility-scale solar energy improves social welfare. Previous studies have not developed a cost-benefit analysis framework based on a comprehensive life cycle approach. This article closes this knowledge gap. This article aims to develop a comprehensive utility-scale solar energy cost-benefit analysis framework. This article critically reviews the previous literature on the topic of cost-benefit analysis of utility-scale solar energy. Finally, this article proposes an analytical framework and some further research agenda.
Modification of the MTS model for high strain-rate behavior of TI-6AL-4V
Authors: Allen Jason , Garmestani Hamid
Published: August 2023

The Mechanical Threshold Stress (MTS) model provides excellent predictive capabilities for the material constitutive response for a wide range of temperatures and strain rates. However, the MTS model fails to capture the rapidly increasing yield stress at high strain rate behavior as the deformation controlling mechanism transitions from thermal activation to drag mechanisms, only capturing the linear behavior. Further, the model typically over predicts the flow stress behavior at yield and post yield due to its use of a constant work hardening rate parameter derived from the stress–strain response at constant saturation stress. An alternative approach to fitting portions of the MTS model is investigated and mathematical models are developed to address these issues. The results show that with appropriate experimental data, the mechanical threshold stress and work hardening rate parameters within the MTS model can quite easily and accurately be modified to extend applicability to high strain rate behavior and more accurately model the initial flow stress behavior at early work hardening rates without modification of the functions core to the MTS model itself.
C-57 nanotube: electronic, optical, and mechanical properties by DFT calculations
Authors: Asadpour Mohammad , Jafari Mahmoud
Published: August 2023

Electronic, optical, and mechanical properties of single-walled C-57 carbon nanotube have been investigated within the framework of density functional theory (DFT). It was found that for the nanotube, there is a direct relationship between its radius and Young’s modulus: larger radius leads to larger Young’s modulus. Optical properties have been calculated within a NORMCONS pseudopotential type (Von Barth–Car Method) whit Perdew–Zunger (LDA) exch-correlation scalar relativistic functional type, showing that decrease in radius of the nanotube increases both static refractive index and dielectric constant is increased. Examining band structure and density of states (DOS) further reveals that this nanotube is a metallic carbon allotrope. The potential ability of lithium (Li) and sodium (Na) adsorption on single-layer C-57 nanotube has also been evaluated at vdW-DF3-OPT2, PBEsol and DFT-D3 levels of theory. Preferred Li or Na adsorption sites have accordingly been identified in terms of adsorption energy; and geometries of 1 up to 4 adsorbed Li or Na atoms on the outside of the nanotube was also studied. Results of the adsorption energy and the open circuit voltage (OCV) showed that this nanostructure could be a suitable material for lithium or sodium storage. In addition, suitable theoretical storage capacity (278.92 mAh g−1) was obtained as an anode material.
Certification and applications of quantum nonlocal correlations
Authors: Piceno-Martínez A Elena , Rosales-Zárate Laura E C , Ornelas-Cruces P
Published: August 2023

Entanglement and Einstein–Podolsky–Rosen (EPR) steering are nonlocal quantum correlations, which are relevant resources for quantum information protocols. EPR steering, or quantum steering, refers to the correlation where a party might ‘steer’, or modify, the state of another, which is spatially separated. Entanglement is a symmetric resource while steering is asymmetrical, since it depends on the direction of the effect. Due to these different characteristics and the therefore different possible applications, there has been both theoretical and experimental research on forms to certify the distinct quantum nonlocal correlations. In recent years, alongside the investigation on quantum correlations between two systems, there has been a great interest in investigating multipartite/multimode entanglement as well as steering, since they include a high dimension and it may be possible to store more information than in a single qubit. In this review, we will summarize the different criteria and measures that have been developed for the characterization of these two kinds of correlations. We first focus on bipartite entanglement and steering. We then review the progress that has been made in the investigation of multipartite quantum correlations. We revise the theoretical work in quantum nonlocal correlation witnesses and measures, which respectively allow one to certify that the system is entangled or presents EPR steering, and give a quantification of the content of these correlations in the system. Then, we briefly review the experiments that have been designed and that demonstrate multipartite quantum correlations. We also include applications in quantum information protocols, in particular in quantum teleportation and quantum cryptography.
Comparing the impacts of ozone-depleting substances and carbon dioxide on Arctic sea ice loss
Authors: Bushuk Mitchell , Polvani Lorenzo M , England Mark R
Published: August 2023

The rapid decline of Arctic sea ice is widely believed to be a consequence of increasing atmospheric concentrations of greenhouse gases (GHGs). While carbon dioxide (CO2) is the dominant GHG contributor, recent work has highlighted a substantial role for ozone-depleting substances (ODS) in Arctic sea ice loss. However, a careful analysis of the mechanisms and relative impacts of CO2 versus ODS on Arctic sea ice loss has yet to be performed. This study performs this comparison over the period 1955–2005 when concentrations of ODS increased rapidly, by analyzing a suite of all-but-one-forcing ensembles of climate model integrations, designed to isolate the forced response to individual forcing agents in the context of internal climate variability. We show that ODS have played a significant role in year-round Arctic sea ice extent and volume trends over that period, accounting for 64% and 32% of extent and volume trends, respectively. These impacts represent 50% and 38% of the impact from CO2 forcing, respectively. We find that ODS act via similar physical processes to CO2, causing sea ice loss via increased summer melt, and not sea ice dynamics changes. These findings imply that the future trajectory of ODS emissions will play an important role in future Arctic sea ice evolution.
TV Cloning as Transcultural Adaptation: The Reformatting of the Medea Myth viaDoctor Foster
Authors: Voigts Eckart , Park-Finch Heebon
Published: August 2023

This special issue asks the question of what new digital technologies bring to the re-telling of old stories. In our contribution, we discuss how the practice of TV cloning on transnational digital streaming platforms has affected almost a decade of remixing and reformatting the Medea myth. In 2015, British playwright Mike Bartlett, best known for his work in theatre, adapted Medea to British television. The resulting BBC production Doctor Foster was a hit and spawned a second series in 2017. Subsequently Doctor Foster became a global phenomenon as it was remade in a variety of surprisingly diverse cultural milieus. The localized adaptations of Doctor Foster are cases of franchise diversification and expansion that gave new traction to the tradition of ‘programme adaptation’ (Keane/Moran) and has been dubbed ‘TV formatting’ (Moran/Malbon, Miller) or ‘TV cloning’ (Fung/Zhang). They are not a new phenomenon, as early 21st century precursors predate the world of television streaming or what Amanda Lotz has called ‘internet-distributed television’, but the diversified world of platform TV seems ideally suited to the practice of TV cloning. According to Michael Keane and Albert Moran (6) the format is ‘the total package of information and know-how that increases the adaptability of a program in another place and time’. Possession of the format enables producers to grant licenses and enforce copyright. The context for this study that seeks to address both the emerging textualities and practices of these digitally transformed TV industries is the fluid redistribution of television consumption zones across the planet.
Anatomical Considerations for the Injection of Botulinum Neurotoxin in Shoulder and Arm Contouring
Authors: Yi Kyu-Ho , Choi You-Jin , Lee Ji-Hyun , Hu Hyewon , Gil Young-Chun , Hu Kyung-Seok , Kim Hee-Jin
Published: August 2023

The utilization of botulinum neurotoxin in the field of body contouring is on the rise. Body contouring procedures typically focus on specific muscle groups such as the superior trapezius, deltoid, and lateral head of the triceps brachii. The authors propose identifying optimal injection sites for botulinum neurotoxin to achieve desired aesthetic contouring of the shoulders and arms. The authors conducted a modified Sihler’s staining method on specimens of the superior trapezius, deltoid, and lateral head of the triceps brachii muscles, totaling 16, 14, and 16 specimens, respectively. The neural distribution exhibited the most extensive branching patterns within the horizontal section (between 1/5 and 2/5) and the vertical section (between 2/4 and 4/4) of the superior trapezius muscle. In the deltoid muscle, the areas between the anterior and posterior deltoid bellies, specifically within the range of the horizontal 1/3 to 2/3 lines, showed significant intramuscular arborization. Furthermore, the middle deltoid muscle displayed arborization patterns between 2/3 and the axillary line. Regarding the triceps brachii muscle, the lateral heads demonstrated arborization between 4/10 and 7/10. The authors recommend targeting these regions, where maximum arborization occurs, as the optimal and safest points for injecting botulinum toxin.
DELFMUT: duplex sequencing-oriented depth estimation model for stable detection of low-frequency mutations
Authors: Wu Guiying , Song Mengmeng , Wang Ke , Cui Tianyu , Jiao Zicong , Ji Liyan , Gao Xuan , Wang Jiayin , Liu Tao , Xia Xuefeng , Fang Huan , Guan Yanfang , Yi Xin
Published: August 2023

Duplex sequencing technology has been widely used in the detection of low-frequency mutations in circulating tumor deoxyribonucleic acid (DNA), but how to determine the sequencing depth and other experimental parameters to ensure the stable detection of low-frequency mutations is still an urgent problem to be solved. The mutation detection rules of duplex sequencing constrain not only the number of mutated templates but also the number of mutation-supportive reads corresponding to each forward and reverse strand of the mutated templates. To tackle this problem, we proposed a Depth Estimation model for stable detection of Low-Frequency MUTations in duplex sequencing (DELFMUT), which models the identity correspondence and quantitative relationships between templates and reads using the zero-truncated negative binomial distribution without considering the sequences composed of bases. The results of DELFMUT were verified by real duplex sequencing data. In the case of known mutation frequency and mutation detection rule, DELFMUT can recommend the combinations of DNA input and sequencing depth to guarantee the stable detection of mutations, and it has a great application value in guiding the experimental parameter setting of duplex sequencing technology.
HEAP: a task adaptive-based explainable deep learning framework for enhancer activity prediction
Authors: Liu Yuhang , Wang Zixuan , Yuan Hao , Zhu Guiquan , Zhang Yongqing
Published: August 2023

Enhancers are crucial cis-regulatory elements that control gene expression in a cell-type-specific manner. Despite extensive genetic and computational studies, accurately predicting enhancer activity in different cell types remains a challenge, and the grammar of enhancers is still poorly understood. Here, we present HEAP (high-resolution enhancer activity prediction), an explainable deep learning framework for predicting enhancers and exploring enhancer grammar. The framework includes three modules that use grammar-based reasoning for enhancer prediction. The algorithm can incorporate DNA sequences and epigenetic modifications to obtain better accuracy. We use a novel two-step multi-task learning method, task adaptive parameter sharing (TAPS), to efficiently predict enhancers in different cell types. We first train a shared model with all cell-type datasets. Then we adapt to specific tasks by adding several task-specific subset layers. Experiments demonstrate that HEAP outperforms published methods and showcases the effectiveness of the TAPS, especially for those with limited training samples. Notably, the explainable framework HEAP utilizes post-hoc interpretation to provide insights into the prediction mechanisms from three perspectives: data, model architecture and algorithm, leading to a better understanding of model decisions and enhancer grammar. To the best of our knowledge, HEAP will be a valuable tool for insight into the complex mechanisms of enhancer activity.
NCOurd: modelling length distributions of NCO events and gene conversion tracts
Authors: Hardarson Marteinn T , Palsson Gunnar , Halldorsson Bjarni V
Published: August 2023

Motivation

Meiotic recombination is the main driving force of human genetic diversity, along with mutations. Recombinations split into crossovers, separating large chromosomal regions originating from different homologous chromosomes, and non-crossovers (NCOs), where a small segment from one chromosome is embedded in a region originating from the homologous chromosome. NCOs are much less studied than mutations and crossovers as NCOs are short and can only be detected at markers heterozygous in the transmitting parent, leaving most of them undetectable.

Results

The detectable NCOs, known as gene conversions, hide information about NCOs, including their number and length, waiting to be unveiled. We introduce NCOurd, software, and algorithm, based on an expectation–maximization algorithm, to estimate the number of NCOs and their length distribution from gene conversion data.

Availability and implementation

https://github.com/DecodeGenetics/NCOurd
ProtoCell4P: an explainable prototype-based neural network for patient classification using single-cell RNA-seq
Authors: Xiong Guangzhi , Bekiranov Stefan , Zhang Aidong
Published: August 2023

Motivation

The rapid advance in single-cell RNA sequencing (scRNA-seq) technology over the past decade has provided a rich resource of gene expression profiles of single cells measured on patients, facilitating the study of many biological questions at the single-cell level. One intriguing research is to study the single cells which play critical roles in the phenotypes of patients, which has the potential to identify those cells and genes driving the disease phenotypes. To this end, deep learning models are expected to well encode the single-cell information and achieve precise prediction of patients’ phenotypes using scRNA-seq data. However, we are facing critical challenges in designing deep learning models for classifying patient samples due to (i) the samples collected in the same dataset contain a variable number of cells—some samples might only have hundreds of cells sequenced while others could have thousands of cells, and (ii) the number of samples available is typically small and the expression profile of each cell is noisy and extremely high-dimensional. Moreover, the black-box nature of existing deep learning models makes it difficult for the researchers to interpret the models and extract useful knowledge from them.

Results

We propose a prototype-based and cell-informed model for patient phenotype classification, termed ProtoCell4P, that can alleviate problems of the sample scarcity and the diverse number of cells by leveraging the cell knowledge with representatives of cells (called prototypes), and precisely classify the patients by adaptively incorporating information from different cells. Moreover, this classification process can be explicitly interpreted by identifying the key cells for decision making and by further summarizing the knowledge of cell types to unravel the biological nature of the classification. Our approach is explainable at the single-cell resolution which can identify the key cells in each patient’s classification. The experimental results demonstrate that our proposed method can effectively deal with patient classifications using single-cell data and outperforms the existing approaches. Furthermore, our approach is able to uncover the association between cell types and biological classes of interest from a data-driven perspective.

Availability and implementation

https://github.com/Teddy-XiongGZ/ProtoCell4P.
Enhancing cryo-EM maps with 3D deep generative networks for assisting protein structure modeling
Authors: Maddhuri Venkata Subramaniya Sai Raghavendra , Terashi Genki , Kihara Daisuke
Published: August 2023

Motivation

The tertiary structures of an increasing number of biological macromolecules have been determined using cryo-electron microscopy (cryo-EM). However, there are still many cases where the resolution is not high enough to model the molecular structures with standard computational tools. If the resolution obtained is near the empirical borderline (3–4.5 Å), improvement in the map quality facilitates structure modeling.

Results

We report EM-GAN, a novel approach that modifies an input cryo-EM map to assist protein structure modeling. The method uses a 3D generative adversarial network (GAN) that has been trained on high- and low-resolution density maps to learn the density patterns, and modifies the input map to enhance its suitability for modeling. The method was tested extensively on a dataset of 65 EM maps in the resolution range of 3–6 Å and showed substantial improvements in structure modeling using popular protein structure modeling tools.

Availability and implementation

https://github.com/kiharalab/EM-GAN, Google Colab: https://tinyurl.com/3ccxpttx.
Few-shot biomedical named entity recognition via knowledge-guided instance generation and prompt contrastive learning
Authors: Chen Peng , Wang Jian , Lin Hongfei , Zhao Di , Yang Zhihao
Published: August 2023

Motivation

Few-shot learning that can effectively perform named entity recognition in low-resource scenarios has raised growing attention, but it has not been widely studied yet in the biomedical field. In contrast to high-resource domains, biomedical named entity recognition (BioNER) often encounters limited human-labeled data in real-world scenarios, leading to poor generalization performance when training only a few labeled instances. Recent approaches either leverage cross-domain high-resource data or fine-tune the pre-trained masked language model using limited labeled samples to generate new synthetic data, which is easily stuck in domain shift problems or yields low-quality synthetic data. Therefore, in this article, we study a more realistic scenario, i.e. few-shot learning for BioNER.

Results

Leveraging the domain knowledge graph, we propose knowledge-guided instance generation for few-shot BioNER, which generates diverse and novel entities based on similar semantic relations of neighbor nodes. In addition, by introducing question prompt, we cast BioNER as question-answering task and propose prompt contrastive learning to improve the robustness of the model by measuring the mutual information between query–answer pairs. Extensive experiments conducted on various few-shot settings show that the proposed framework achieves superior performance. Particularly, in a low-resource scenario with only 20 samples, our approach substantially outperforms recent state-of-the-art models on four benchmark datasets, achieving an average improvement of up to 7.1% F1.

Availability and implementation

Our source code and data are available at https://github.com/cpmss521/KGPC.
CDNM: Clustering-Based Data Normalization Method For Automated Vulnerability Detection
Authors: Wu Tongshuai , Chen Liwei , Du Gewangzi , Zhu Chenguang , Cui Ningning , Shi Gang
Published: August 2023

The key to deep learning vulnerability detection framework is pre-processing source code and learning vulnerability features. Traditional source code representation techniques take a complete normalization to user-defined symbols but ignore the semantic information associated with vulnerabilities. The current mainstream vulnerability feature learning model is Recurrent Neural Network (RNN), whose time-series structure determines its insufficient remote information acquisition capability. This paper proposes a new vulnerability detection framework to solve the above problems. We propose a new data normalization method in the source code pre-processing phase. The user-defined symbols are clustered using the unsupervised clustering algorithm K-means. The normalized classification is performed according to the clustering results, which preserves the primary semantic information in the source code and ensures the smoothness of the sample data. In the feature extraction stage, we input the source code after performing text representation into Bidirectional Encoder Representations for Transformers (BERT) for feature automation learning, which enhances semantic information extraction and remote information acquisition. Experimental results show that the vulnerability detection precision of this method is 18.3% higher than that of the current mainstream vulnerability detection framework in the real-world data collected by ourselves. Further, our method improves the precision of the state-of-the-art method by 4.2%.
Causal Roles of Lifestyle, Psychosocial Characteristics, and Sleep Status in Sarcopenia: A Mendelian Randomization Study
Authors: Liu Mingchong , Yu Daqian , Pan Yutao , Ji Shengchao , Han Ning , Yang Chensong , Sun Guixin
Published: August 2023

Background

Many studies reported that lifestyle, psychosocial characteristics, and sleep status related to sarcopenia, although few studies provided evidence of causal relationships between them.

Methods

The data used in our study were from UK Biobank, FinnGen Release 8, and large genome-wide association study meta-analyses. Two-sample Mendelian randomization was conducted to identify the causal associations of 21 traits of lifestyle, psychosocial characteristics, and sleep status with 6 traits of sarcopenia. Benjamini–Hochberg correction was performed to reduce the bias caused by multiple tests. Risk factor analyses were performed to explore the potential mechanism behind the exposures.

Results

Mendelian randomization analyses after adjustment proved the causal roles of coffee intake, education years, smoking, leisure screen time, and moderate-to-vigorous intensity physical activity during leisure time in sarcopenia was proven although providing no significant evidence for causal roles for carbohydrates intake, protein intake, alcohol, and sleep status in sarcopenia.

Conclusions

Our results strongly support that coffee intake, education years, smoking, leisure screen time, and moderate-to-vigorous intensity physical activity during leisure time played significantly causal roles in sarcopenia, which may provide new intervention strategies for preventing the development of sarcopenia.
Commercial coverage of specialty drugs, 2017–2021
Authors: Rucker Julia A , Beinfeld Molly T , Jenkins Nola B , Enright Daniel E , Henderson Rochelle R , Chambers James D
Published: August 2023

Health plans guide their enrollees’ access to specialty drugs through coverage policies. We examined a set of health plan policies to determine if they have become more or less stringent over time. We did so by comparing the consistency of policies with Food and Drug Administration (FDA) label indications. We considered coverage policies for the same 187 specialty drugs issued by 17 large US commercial health plans from 2017 through 2021. Overall, the proportion of policies that were consistent with the FDA label declined from 57.1% in 2017 to 45.1% in 2021; the proportion of policies that were more restrictive than the FDA label increased from 39.5% to 51.7%. The proportion of policies excluding drug coverage remained approximately constant (3.4% in 2017; 3.2% in 2021). Trends in coverage restrictiveness varied across plans. For 13 plans, the proportion of policies with restrictions increased over time, while for 4 plans it declined.
CmoNAC1 in pumpkin rootstocks improves salt tolerance of grafted cucumbers by binding to the promoters of CmoRBOHD1, CmoNCED6, CmoAKT1;2 and CmoHKT1;1 to regulate H2O2, ABA signaling and K+/Na+ homeostasis
Authors: Peng Yuquan , Cao Haishun , Cui Lvjun , Wang Ying , Wei Lanxing , Geng Shouyu , Yang Li , Huang Yuan , Bie Zhilong
Published: August 2023

The NAC transcription factor is a type of plant-specific transcription factor that can regulate plant salt tolerance, but the underlying mechanism is unclear in grafted vegetables. H2O2 and ABA in pumpkin rootstocks can be transported to cucumber scion leaves, promoting stomatal closure to improve salt tolerance of grafted cucumbers. Despite these observations, the regulatory mechanism is unknown. Here, our research revealed that CmoNAC1 is a key transcription factor that regulates H2O2 and ABA signaling in pumpkin roots under salt stress. The function of CmoNAC1 was analyzed using root transformation and RNA-seq, and we found that pumpkin CmoNAC1 promoted the production of H2O2 and ABA via CmoRBOHD1 and CmoNCED6, respectively, and regulated K+/Na+ homeostasis via CmoAKT1;2, CmoHKT1;1, and CmoSOS1 to improve salt tolerance of grafted cucumbers. Root knockout of CmoNAC1 resulted in a significant decrease in H2O2 (52.9% and 32.1%) and ABA (21.8% and 42.7%) content and K+/Na+ ratio (81.5% and 56.3%) in leaf and roots of grafted cucumber, respectively, while overexpression showed the opposite effect. The root transformation experiment showed that CmoNCED6 could improve salt tolerance of grafted cucumbers by regulating ABA production and K+/Na+ homeostasis under salt stress. Finally, we found that CmoNAC1 bound to the promoters of CmoRBOHD1, CmoNCED6, CmoAKT1;2, and CmoHKT1;1 using yeast one-hybrid, luciferase, and electrophoretic mobility shift assays. In conclusion, pumpkin CmoNAC1 not only binds to the promoters of CmoRBOHD1 and CmoNCED6 to regulate the production of H2O2 and ABA signals in roots, but also binds to the promoters of CmoAKT1;2 and CmoHKT1;1 to increase the K+/Na+ ratio, thus improving salt tolerance of grafted cucumbers.
Rising to the Challenge: Mounting an Acute Phase Immune Response Has No Long-Term Negative Effects on Captive Sparrow Migratory Body Composition or Migratory Restlessness
Authors: Kelly T R , Butnari A C , MacDougall-Shackleton E A , MacDougall-Shackleton S A
Published: August 2023

Synopsis

Migratory animals may trade-off between investing energy in immune defense versus investing in energy reserves needed for seasonal migration. However, these trade-offs are often masked by other sources of variation and may not be detected through observational field studies of free-living animals. Moreover, observational studies can rarely distinguish the costs of pathogenic infection from those of mounting an immune response. To disentangle such effects, we conducted an immune challenge experiment. We captured song sparrows (Melospiza melodia) and white-throated sparrows (Zonotrichia albicollis) in autumn migratory condition, challenged the sparrows with non-infectious antigens that induce an acute-phase immune response, then monitored body composition and migratory restlessness behavior. For both species, body mass was higher the day after exposure to keyhole limpet hemocyanin (KLH) compared to controls. White-throated sparrows, but not song sparrows, increased lean mass 1 week after exposure to lipopolysaccharide (LPS), suggesting that effects of immune upregulation on body composition may be long-lasting and specific to certain combinations of hosts and antigens. White-throated sparrows exposed to KLH increased nocturnal migratory restlessness (Zugunruhe) for the week following exposure. These findings suggest that short-term activation of the acute immune response does not constrain migratory physiology in these songbirds.
Stable Isomorphisms of Operator Algebras
Authors: Kakariadis Evgenios T A , Katsoulis Elias G , Li Xin
Published: August 2023

Let ${{\mathcal{A}}}$ and ${{\mathcal{B}}}$ be operator algebras with $c_{0}$-isomorphic diagonals and let ${{\mathcal{K}}}$ denote the compact operators. We show that if ${{\mathcal{A}}}\otimes{{\mathcal{K}}}$ and ${{\mathcal{B}}}\otimes{{\mathcal{K}}}$ are isometrically isomorphic, then ${{\mathcal{A}}}$ and ${{\mathcal{B}}}$ are isometrically isomorphic. If the algebras ${{\mathcal{A}}}$ and ${{\mathcal{B}}}$ satisfy an extra analyticity condition a similar result holds with ${{\mathcal{K}}}$ being replaced by any operator algebra containing the compact operators. For nonselfadjoint graph algebras this implies that the graph is a complete invariant for various types of isomorphisms, including stable isomorphisms, thus strengthening a recent result of Dor-On, Eilers, and Geffen. Similar results are proven for algebras whose diagonals satisfy cancellation and have $K_{0}$-groups isomorphic to ${{\mathbb{Z}}}$. This has implications in the study of stable isomorphisms between various semicrossed products.