Miracle-dz/UniFAR-FTUs huggingface dataset:
Solar cycle changes in the ionization sources of the nightside Venus ionosphere

Using new and previous experimental evidence, it is argued that the height-integrated flux of O(+) ions transported from the dayside Venus ionosphere into the nightside ionosphere is strongly reduced (shut off) at solar cycle minimum (SCmin) and that the electron impact source becomes the predominant nightside ionization source during this phase of the solar cycle. The height-integrated transterminator O(+) flux, which is probably the dominant nightside ionization source at solar cycle maximum (SCmax), is shut off at SCmin by compression of the dayside ionopause to low altitude. It is suggested that the ionopause is depressed because the dayside ionospheric kinetic pressure field is reduced by a factor of approximately 3 from its SCmas value and that the typical SCmin solar wind dynamic pressure, which is not less than the typical SCmax value, cannot be balanced by the ionospheric pressure field at altitudes above approximately 250 km.
Wearable ankle assistance robot for a human walking with different loads

Abstract. To reduce energy consumption while a human is walking with different loads, an active energy storage mechanism and a gait cycle prediction method are proposed, and then a wearable ankle assistance robot is developed. A motor, a clutch, and elastic rods are placed strategically in the active energy storage mechanism to achieve energy storage and release. During the period when the ankle does not generate torque, the clutch is closed, and the elastic rods are driven by the motor to produce deformation for energy storage. When the ankle generates torque, the motor is stopped and the clutch is opened, and then energy is released. Assisted force is transmitted to the human heel by a flexible transmission device to achieve walking assistance. The deformation length of the elastic rods can be changed to achieve assisted force adjustment for different loads. Based on the hip angular displacement and heel pressure, the gait cycle can be obtained with the proposed prediction method, and then assistance control can be achieved. Consequently, the development of a wearable ankle assistance robot is realized, a walking assistance experiment with different loads is completed, and the net metabolic cost is used to indicate the energy consumption. The experimental results show that the net metabolic cost of the participants is reduced by averages of 5.30 %, 5.67 %, and 4.84 % with 0, 4, and 8 kg loads respectively. The reduced net metabolic costs are compared with other research results; the reduced net metabolic costs are close to the others, but the motor power in this work is lower.
An Explainable Ensemble Deep Learning Approach for Intrusion Detection in Industrial Internet of Things

Ensuring the security of critical Industrial Internet of Things (IIoT) systems is of utmost importance, with a primary focus on identifying cyber-attacks using Intrusion Detection Systems (IDS). Deep learning (DL) techniques are frequently utilized in the anomaly detection components of IDSs. However, these models often generate high false-positive rates, and their decision-making rationale remains opaque, even to experts. Gaining insights into the reasons behind an IDS’s decision to block a specific packet can aid cybersecurity professionals in assessing the system’s effectiveness and creating more cyber-resilient solutions. In this paper, we offer an explainable ensemble DL-based IDS to improve the transparency and robustness of DL-based IDSs in IIoT networks. The framework incorporates Shapley additive explanations (SHAP) and Local comprehensible-independent Clarifications (LIME) methods to elucidate the decisions made by DL-based IDSs, providing valuable insights to experts responsible for maintaining IIoT network security and developing more cyber-resilient systems. The ToN_IoT dataset was used to evaluate the efficacy of the suggested framework. As a baseline intrusion detection system, the extreme learning machines (ELM) model was implemented and compared with other models. Experiments show the effectiveness of ensemble learning to improve the results.
Evolutionary Adaptation of Protein Turnover in White Muscle of Stenothermal Antarctic Fish: Elevated Cold Compensation at Reduced Thermal Responsiveness

Protein turnover is highly energy consuming and overall relates to an organism’s growth performance varying largely between species, e.g., due to pre-adaptation to environmental characteristics such as temperature. Here, we determined protein synthesis rates and capacity of protein degradation in white muscle of the cold stenothermal Antarctic eelpout (Pachycara brachycephalum) and its closely related temperate counterpart, the eurythermal common eelpout (Zoarces viviparus). Both species were exposed to acute warming (P. brachycephalum, 0 °C + 2 °C day−1; Z. viviparus, 4 °C + 3 °C day−1). The in vivo protein synthesis rate (Ks) was monitored after injection of 13C-phenylalanine, and protein degradation capacity was quantified by measuring the activity of cathepsin D in vitro. Untargeted metabolic profiling by nuclear magnetic resonance (NMR) spectroscopy was used to identify the metabolic processes involved. Independent of temperature, the protein synthesis rate was higher in P. brachycephalum (Ks = 0.38–0.614 % day−1) than in Z. viviparus (Ks= 0.148–0.379% day−1). Whereas protein synthesis remained unaffected by temperature in the Antarctic species, protein synthesis in Z. viviparus increased to near the thermal optimum (16 °C) and tended to fall at higher temperatures. Most strikingly, capacities for protein degradation were about ten times higher in the Antarctic compared to the temperate species. These differences are mirrored in the metabolic profiles, with significantly higher levels of complex and essential amino acids in the free cytosolic pool of the Antarctic congener. Together, the results clearly indicate a highly cold-compensated protein turnover in the Antarctic eelpout compared to its temperate confamilial. Constant versus variable environments are mirrored in rigid versus plastic functional responses of the protein synthesis machinery.
Seawater Radiocarbon Evolution in the Gulf of Alaska: 2002 Observations

Oceanic uptake and transport of bomb radiocarbon as 14CO2 created by atmospheric nuclear weapons testing in the 1950s and 1960s has been a useful diagnostic for determining the carbon transfer between the ocean and atmosphere. In addition, the distribution of 14C in the ocean can be used as a tracer of oceanic circulation. Results obtained on samples collected in the Gulf of Alaska in the summer of 2002 provide a direct comparison with results in the 1970s during GEOSECS and in the early 1990s during WOCE. The open gyre values are 20–40% lower than those documented in 1991 and 1993 (WOCE), although the general trends as a function of latitude are reproduced. Surface values are still significantly higher than pre-bomb levels (∼ −105% or lower). In the central gyre, we observe Δ14C values that are lower in comparison to GEOSECS (stn 218) and WOCE P16/P17 to a density of ∼26.8 σt. This observation is consistent with the overall decrease in surface Δ14C values and reflects the erosion of the bomb-14C transient. We propose that erosion of the bomb-14C transient is accomplished by entrainment of low-14C water via vertical exchange within the Gulf of Alaska and replenishment of surface and subther-mocline waters with waters derived from the far northwest Pacific.
Weathering: Cyclical or continuous? An Australian perspective

A study of the age distribution of existing weathering profiles and related ferruginous products on the Australian continent was undertaken using information from published and unpublished sources. The age distribution of existing weathering profiles follows an increasing trend towards the present, which can be approximately represented by an exponential curve. This corresponds to similar trends relating to most other geological entities on earth and can be correlated with the process of recycling, that is, destruction over time and rebirth, possibly in another form. In accordance with general theory and past assumptions, a possible increase in weathering was observed at the beginning of the Tertiary, although this was much less significant than previous studies claimed. There is now reasonable evidence to suggest that such deviations from long‐term trends may have occurred as a consequence of increases in the potential for preservation rather than as a direct result of climate influence, despite the well‐known effect that precipitation has on weathering. A broad range of dates from Permian to the present, within a consortium of recognised dating techniques, supports the contention that weathering in Australia has been relatively continuous and did not occur as distinct episodes.
The Water Footprint Assessment Manual: Setting the Global Standard

This manual presents a scientifically rigorous method to help companies understand their dependency and impact on global water resources, and offers guidance on response strategies that conserve water for industry, communities, and nature. It contains the global standard for water footprint assessment as developed and maintained by the Water Footprint Network. It covers a comprehensive set of definitions and methods for water footprint accounting. It shows how water footprints are calculated for individual processes and products, as well as for consumers, nations, and businesses. It also includes methods for water footprint sustainability assessment and a library of water footprint response options. The water footprint of a product is the volume of freshwater used to produce the product, measured over the fully supply chain. It is a multidimensional indicator, showing water consumption volumes by source and polluted volumes by type of pollution; all components of a total water footprint are specified geographically and temporally.
The Characterization of Melanaphis sacchari Microbiota and Antibiotic Treatment Effect on Insects

Simple Summary Insects are rapidly adapting to novel niches, such as crops. This is the case of the sugarcane aphid, a pest from Africa that is currently spreading worldwide. In the absence of males, aphids asexually generate many females, causing important economic losses for farmers. The microbiota in the insect was characterized and the presence of Wolbachia was also reported, correlating with its asexual reproduction. Antibiotic treatment of the aphid population resulted in a decrease in its survival rate. The possibility of controlling this pest by altering its microbiota is proposed in the present work. Abstract Insects are under constant selective pressure, which has resulted in adaptations to novel niches such as crops. This is the case of the pest Melanaphis sacchari, the sugarcane aphid, native to Africa and currently spreading worldwide. The aphid undergoes successful parthenogenesis, causing important damage to a variety of crops and leading to important economic losses for farmers. A natural M. sacchari population grown in sorghum was studied to identify its microbiome through the sequencing of its 16S rDNA metagenome. A high proportion of Proteobacteria, followed by Firmicutes, Bacteroidetes, and Actinobacteria, was observed. We also detected Wolbachia, which correlates with the asexual reproduction of its host. M. sacchari was challenged in a bioassay with the antibiotics oxytetracycline and streptomycin, resulting in a dose-dependent decay of its survival rate. The possibility of controlling this pest by altering its microbiota is proposed.
Spatiotemporal variations of water, land, and carbon footprints of pig production in China

Pig production not only consumes large water and land, but also emits substantial greenhouse gases. Scholars have used environmental footprint, including water, land, and carbon footprints, to assess the environmental impacts of pig production. However, there is a lack of simultaneous analysis of water, land, and carbon footprints for pig production, particularly in China, the leading pig breeding and consumption country in the world. In this study, we used environmental footprint analysis to develop a water-land-carbon footprint model for pig production system from the life cycle perspective. We also examined virtual water, land and carbon flows embedded in trade. The life cycle of pig production mainly involves feed crop cultivation, feed production, and pig breeding. Then we analyzed the water, land, and carbon footprints of the pig production in China from 1990 to 2018. The findings indicated that both the total water footprint and the total land footprint increased, whereas the total carbon footprints fluctuated over the years. All the unit footprints generally decreased. Feed crop cultivation had a significant impact on the footprints. Regarding the spatial characteristics in China, all the three total footprints were generally higher in the southeast compared to the northwest. While the unit footprints in different provinces exhibited spatial heterogeneity, primarily attributed to the different feed consumptions. Overall, the trade of feed crop shifted virtual water, land and carbon flows from the north to the south, reducing the three total footprints on the whole. To achieve a resource-saving and eco-friendly pig production in China, we proposed some potential recommendations, including improving feed crop cultivation techniques, reducing feed conversion ratio, implementing precision feeding, and managing manure. We hope not only mitigate the environmental impacts of China’s pig production, but also provide references for achieving agricultural sustainability in other regions of the world.
Radiomics Analysis in Characterization of Salivary Gland Tumors on MRI: A Systematic Review

Simple Summary This review systematically evaluated radiomics analysis procedures for characterizing salivary gland tumors (SGTs) on magnetic resonance imaging (MRI). Radiomics analysis showed potential for characterizing SGTs on MRI, but its clinical application is limited due to complex procedures and a lack of standardized methods. This review summarized radiomics analysis procedures, focusing on reported methodologies and performances, and proposed potential standards for the procedures for radiomics analysis, which may benefit further developments of radiomics analysis in characterizing SGTs on MRI. Abstract Radiomics analysis can potentially characterize salivary gland tumors (SGTs) on magnetic resonance imaging (MRI). The procedures for radiomics analysis were various, and no consistent performances were reported. This review evaluated the methodologies and performances of studies using radiomics analysis to characterize SGTs on MRI. We systematically reviewed studies published until July 2023, which employed radiomics analysis to characterize SGTs on MRI. In total, 14 of 98 studies were eligible. Each study examined 23–334 benign and 8–56 malignant SGTs. Least absolute shrinkage and selection operator (LASSO) was the most common feature selection method (in eight studies). Eleven studies confirmed the stability of selected features using cross-validation or bootstrap. Nine classifiers were used to build models that achieved area under the curves (AUCs) of 0.74 to 1.00 for characterizing benign and malignant SGTs and 0.80 to 0.96 for characterizing pleomorphic adenomas and Warthin’s tumors. Performances were validated using cross-validation, internal, and external datasets in four, six, and two studies, respectively. No single feature consistently appeared in the final models across the studies. No standardized procedure was used for radiomics analysis in characterizing SGTs on MRIs, and various models were proposed. The need for a standard procedure for radiomics analysis is emphasized.
Genetic control of flowering time and fruit yield in citron watermelon

Flowering time and fruit yield are important traits in watermelon crop improvement. There is limited information on the inheritance and genomic loci underlying flowering time and yield performance, especially in citron watermelon. A total of 125 citron watermelon accessions were evaluated in field trials over two growing seasons for days to male and female flowers, fruit count, fruit weight, and fruit yield. The germplasm was genotyped with more than two million single-nucleotide polymorphism (SNP) markers generated via whole-genome resequencing. Trait mapping was conducted using a genome-wide association study (GWAS). Broad-sense heritability for all traits ranged from moderate to high, indicating that genetic improvement through breeding and selection is feasible. Significant marker-trait associations were uncovered for days to female flower (chromosomes Ca04, Ca05, Ca08, and Ca09), fruit count (on Ca02, Ca03, and Ca05), fruit weight (on Ca02, Ca06, Ca08, Ca10, and Ca11), and fruit yield on chromosomes Ca05, Ca07, and Ca09. The phenotypic variation explained by the significant SNPs ranged from 1.6 to 25.4, highlighting the complex genetic architecture of the evaluated traits. Candidate genes relevant to flowering time and fruit yield component traits were uncovered on chromosomes Ca02, Ca04, Ca05, Ca06, Ca09, and Ca11. These results lay a foundation for marker-assisted trait introgression of flowering time and fruit yield component traits in watermelons.
Oceanic response to midlatitude Rossby waves aloft and its feedback in the lower atmosphere in winter Northern Hemisphere

[1] Midlatitude Rossby waves substantiated in the upper tropospheric (300–200 hPa) potential vorticity field exert significant influences on surface conditions. The physical changes associated with the propagation of Rossby waves are investigated from a climatological perspective, particularly over the oceans. Detailed analysis quantitatively shows that the passing of positive Rossby waves with cyclonic vortexes increases net shortwave and longwave radiation over an ocean's surface by promoting a clearer sky condition. Further, the reduced humidity and temperature above the sea surface increases latent and sensible heat fluxes. The increased latent and sensible heat fluxes, in turn, induce secondary atmospheric circulation, characterized by anticyclonic and divergent motion in the lower atmospheric layer above the sea surface. Although the increased latent and sensible heat fluxes may change sea surface temperatures, the complexity of ocean dynamics with complicated land–ocean configurations and the mismatch of the temporal and spatial scales of atmospheric and oceanic motions smears the footprint of Rossby waves.
Eustatic control of turbidites and winnowed turbidites

Global changes in sea level, primarily the results of tectonism and glaciation, control deep-sea sedimentation. During periods of low sea level the frequency of turbidity currents is greatly increased. Episodes of low sea level also cause vigorous contour currents, which winnow away the fines of turbidites. In the rock record, the occurrence of most turbidites and winnowed turbidites closely corresponds to global lowstands of paleo-sea level. This observation may be useful in predicting the occurrence of deep-sea reservoir facies in the geologic record.
A motor imagery EEG classification algorithm based on ResCNN-BiGRU

In recent years, deep learning-based methods for motor imagery EEG classification have become increasingly popular in the field of brain-computer interfaces. However, most of the studies tend to use sequence-structured classification networks to extract spatial features when dealing with motor imagery EEG signal classification tasks, ignoring the fact that EEG signals as time-series signals contain rich temporal information and features between neural network layers, resulting in poor classification performance. Therefore, this paper proposes a feature fusion network called ResCNNBiGRU, which consists of ResNet-based residual convolutional neural network (ResCNN) and bidirectional gated recurrent unit (BiGRU) connected in parallel. The two branches use different forms of EEG signal feature representation as input, the input to the ResCNN branch is a wavelet transformed time-frequency image, and the input to the BiGRU branch is EEG data in a two-dimensional matrix format. ResCNN extracts spatial features and utilizes interlayer features through residual connections. It also introduces convolutional block attention module (CBAM) to avoid introducing too much useless low-level feature information during interlayer feature fusion. BiGRU extracts temporal features. Finally, experiments are conducted on the authoritative four-category motor imagery dataset BCI Competition IV 2a to verify the performance of the proposed algorithm.
From bench to bedside – current clinical and translational challenges in fibula free flap reconstruction

Fibula free flaps (FFF) represent a working horse for different reconstructive scenarios in facial surgery. While FFF were initially established for mandible reconstruction, advancements in planning for microsurgical techniques have paved the way toward a broader spectrum of indications, including maxillary defects. Essential factors to improve patient outcomes following FFF include minimal donor site morbidity, adequate bone length, and dual blood supply. Yet, persisting clinical and translational challenges hamper the effectiveness of FFF. In the preoperative phase, virtual surgical planning and artificial intelligence tools carry untapped potential, while the intraoperative role of individualized surgical templates and bioprinted prostheses remains to be summarized. Further, the integration of novel flap monitoring technologies into postoperative patient management has been subject to translational and clinical research efforts. Overall, there is a paucity of studies condensing the body of knowledge on emerging technologies and techniques in FFF surgery. Herein, we aim to review current challenges and solution possibilities in FFF. This line of research may serve as a pocket guide on cutting-edge developments and facilitate future targeted research in FFF.
Advances in knowledge-based dynamic capabilities: A systematic review of foundations and determinants in recent literature

Abstract In contemporary dynamic and turbulent competitive business landscape, knowledge-based competition became a new normal. So far, studies gave little attention to an integration of knowledge and dynamic capabilities for business strategies, however. Therefore, this study was initiated to see recent literature developments in knowledge-based dynamic capabilities (KBDCs) as juxtaposition of both themes to identify foundational sources, factors impacting, and consequences by conducting a systematic review. The review considered 72 empirical papers published from 1 January 2015 to 19 July 2022. The findings indicated that tacit knowledge resource, knowledge management, managerial features (team composition, technological insight, and tenure), intellectual/human capital, organizational design/structure, financial resources, social capital, technology ownership and usage, existing operational and dynamic capabilities, and firm location are the foundations of KBDCs. Contextual factors affecting KBDCs at corporate interior are namely firm size, type, realized absorptive capacity, and experiential and organizational knowledge. Those external factors are new technologies, global competition, market dynamism, local business ecosystem, public innovation intermediaries, economic circumstances, and regulatory factors. Businesses used KBDCs’ gained sustainable competitive advantage, improvement in resource base, and proficient in firm’s business performance. Theoretical contributions, implications to practitioners, and future lines of research were discussed.