Miracle-dz/UniFAR-FTUs huggingface dataset:
Algorithms for Right-sizing Heterogeneous Data Centers

Power consumption is a dominant and still growing cost factor in data centers. In time periods with low load, the energy consumption can be reduced by powering down unused servers. We resort to a model introduced by Lin, Wierman, Andrew, and Thereska [23, 24] that considers data centers with identical machines and generalize it to heterogeneous data centers with d different server types. The operating cost of a server depends on its load and is modeled by an increasing, convex function for each server type. In contrast to earlier work, we consider the discrete setting, where the number of active servers must be integral. Thereby, we seek truly feasible solutions. For homogeneous data centers (d=1), both the offline and the online problem were solved optimally in References [3, 4]. In this article, we study heterogeneous data centers with general time-dependent operating cost functions. We develop an online algorithm based on a work function approach that achieves a competitive ratio of 2d + 1 + ε for any ε > 0. For time-independent operating cost functions, the competitive ratio can be reduced to 2d + 1. There is a lower bound of 2d shown in Reference [5], so our algorithm is nearly optimal. For the offline version, we give a graph-based (1+ε)-approximation algorithm. Additionally, our offline algorithm is able to handle time-variable data-center sizes.
From Simulation to Digital Twins, the Case of Internet of Things Research and Tools

The digitalisation of the environment surrounding human beings in their daily life is a major challenge facing today’s technological progress. Building digital replicas of humans and systems help us to understand our environment, to anticipate its variations and to better explain its behaviour. Research in digital twins is continuously developing due to the various benefits it offers. This paper describes how the simulation and modelling community is switching towards digital twins using smart cities as a use case scenario. It also reviews the common digital twin-enabling tools used in today’s research. Finally, the key research trends, challenges and future directions are given.
NeLT: Object-Oriented Neural Light Transfer

This article presents object-oriented neural light transfer (NeLT), a novel neural representation of the dynamic light transportation between an object and the environment. Our method disentangles the global illumination of a scene into individual objects’ light transportation represented via neural networks, then composes them explicitly. It therefore enables flexible rendering with dynamic lighting, cameras, materials, and objects. Our rendering features various important global illumination effects, such as diffuse illumination, glossy illumination, dynamic shadowing, and indirect illumination, which completes the capability of existing neural object representation. Experiments show that NeLT does not require path tracing or shading results as input but achieves rendering quality comparable to state-of-the-art rendering frameworks, including the recent deep learning based denoisers.
Intellectual lidar-based object classification for V2V communication technology implementation

The deep learning techniques have been shown to make a traffic objects classification system for V2V communications to ensure traffic safety and traffic flow prediction. The robust classifier on the base of MLP and PointNet are explored to recognize the traffic objects from lidar point clouds. The features of a lidar sensor, the lidar point cloud coordinate system and its complex properties for creation a smart traffic object detection and recognition model are described. The best configuration of PointNet architecture with hyperparameters are shown, which is more efficient and robust with respect to input perturbation and corruption of lidar point clouds.
Turn-based Spatiotemporal Coherence for GPUs

This article introduces turn-based spatiotemporal coherence. Spatiotemporal coherence is a novel coherence implementation that assigns write permission to epochs (or turns) as opposed to a processor core. This paradigm shift in the assignment of write permissions satisfies all conditions of a coherence protocol with virtually no coherence overhead. We discuss the implementation of this coherence mechanism on a baseline GPU. The evaluation shows that spatiotemporal coherence achieves a speedup of 7.13% for workloads with read data reuse across kernels compared to the baseline software-managed GPU coherence implementation while also providing write atomicity and avoiding the need for software inserted acquire-release operations.1
CROP PRODUCTION UNDER DIFFERENT CLIMATIC CONDITIONS BY ANALYZING AGRICULTURAL DATA USING MULTIPLE LINEAR REGRESSION, WINTER HOLT, AND ARTIFICIAL INTELLIGENCE

The article deals with the prediction of productivity dynamics of agricultural products based on exponential smoothing and optimization using Holt-Winters, multiple linear regression and ANN. Scaling the data is one of the preprocessing steps of the optimization algorithms in the dataset. As we know, most methods of ANN make decisions depending on their underlying data sets. Often, the algorithms calculate the distance between data points to draw better conclusions from the data. The effectiveness of the optimization methods is measured by the average percentage error (MAPE). According to the data calculation results, the Holt-Winter method MAPE value in prediction is 26.129 (), 297 (), 60.384 (), 93.6 (), 52.9 (), and the smallest MAPE value in multiple linear regression method is 0.28, MAPE value for ANN method is 128 Evolved. Considering the level of MAPE, the MAPE value in the ANN method decreased from 685.6 to 93.6 in comparison with other methods. In addition, indicators for multidimensional prediction of agricultural product productivity were developed in Uzbekistan.
The subiculum encodes environmental geometry

Corners are a cardinal feature of many of the complex environmental geometries found in the natural world but the neural substrates that could underlie the perception of corners remain elusive. Here we show that the dorsal subiculum contains neurons that encode corners across environmental geometries in an allocentric reference frame. Corner cells changed their activity to reflect concave corner angles, wall height and the degree of wall intersection. A separate population of subicular neurons encoded convex corners. Both concave and convex corner cells were non-overlapping with subicular neurons that encoded environmental boundaries, suggesting that the subiculum contains the geometric information needed to re-construct the shape and layout of naturalistic spatial environments. One Sentence Summary Separate neural populations in the subiculum encode concave and convex environmental corners.
Neural mechanisms of sequential dependence in time perception: The impact of prior task and memory processing

Our perception and decision-making are susceptible to prior context. Such sequential dependence has been extensively studied in the visual domain, but less is known about its impact on time perception. Moreover, there are ongoing debates about whether these sequential biases occur at the perceptual stage or during subsequent post-perceptual processing. Using functional Magnetic Resonance Imaging (fMRI), we investigated neural mechanisms underlying temporal sequential dependence and the role of action in time judgments across trials. Participants performed a timing task where they had to remember the duration of green coherent motion and were cued to either actively reproduce its duration or simply view it passively. We found that sequential biases in time perception were only evident when the preceding task involved active duration reproduction. Merely encoding a prior duration without reproduction failed to induce such biases. Neurally, we observed activation in networks associated with timing, such as striato-thalamo-cortical circuits, and performance monitoring networks, particularly when a “Response” trial was anticipated. Importantly, the hippocampus showed sensitivity to these sequential biases, and its activation negatively correlated with the individual’s sequential bias following active reproduction trials. These findings highlight the significant role of memory networks in shaping time-related sequential biases at the post-perceptual stages. Significance Statement Our study explores the neural mechanisms of sequential dependence in time perception and reveals that active reproduction of time duration in the previous trial can bias subsequent estimates, resulting in a sequential dependence effect. In contrast, passive viewing of a stimulus without reproducing its duration does not produce this effect. At the neural level, we observed increased activity in memory regions like the hippocampus when sequential biases were reduced. Furthermore, we found a negative correlation between hippocampal activation and sequential bias following active reproduction trials, suggesting that the involvement of memory networks mediates how we are influenced by past experiences when judging time.
PiE: an open-source pipeline for home cage behavioral analysis

Over the last two decades a growing number of neuroscience labs are conducting behavioral assays in rodents. The equipment used to collect this behavioral data must effectively limit environmental and experimenter disruptions, to avoid confounding behavior data. Proprietary behavior boxes are expensive, offer limited compatible sensors, and constrain analysis with closed-source hardware and software. Here, we introduce PiE, an open-source, end-to-end, user-configurable, scalable, and inexpensive behavior assay system. The PiE system includes the custom-built behavior box to hold a home cage, as well as software enabling continuous video recording and individual behavior box environmental control. To limit experimental disruptions, the PiE system allows the control and monitoring of all aspects of a behavioral experiment using a remote web browser, including real-time video feeds. To allow experiments to scale up, the PiE system provides a web interface where any number of boxes can be controlled, and video data easily synchronized to a remote location. For the scoring of behavior video data, the PiE system includes a standalone desktop application that streamlines the blinded manual scoring of large datasets with a focus on quality control and assay flexibility. The PiE system is ideal for all types of behavior assays in which video is recorded. Users are free to use individual components of this setup independently, or to use the entire pipeline from data collection to analysis. Alpha testers have included scientists without prior coding experience. An example pipeline is demonstrated with the PiE system enabling the user to record home cage maternal behavior assays, synchronize the resulting data, conduct blinded scoring, and import the data into R for data visualization and analysis.
B. subtilis MutS2 splits stalled ribosomes into subunits without mRNA cleavage

Stalled ribosomes are rescued by pathways that recycle the ribosome and target the nascent polypeptide for degradation. In E. coli, these pathways are triggered by ribosome collisions through recruitment of SmrB, a nuclease that cleaves the mRNA. In B. subtilis, the related protein MutS2 was recently implicated in ribosome rescue. Here we show that MutS2 is recruited to collisions by its SMR and KOW domains and reveal the interaction of these domains with collided ribosomes by cryo-EM. Using a combination of in vivo and in vitro approaches, we show that MutS2 uses its ABC ATPase activity to split ribosomes, targeting the nascent peptide for degradation by the ribosome quality control pathway. Notably, we see no evidence of mRNA cleavage by MutS2, nor does it promote ribosome rescue by tmRNA as SmrB cleavage does in E. coli. These findings clarify the biochemical and cellular roles of MutS2 in ribosome rescue in B. subtilis and raise questions about how these pathways function differently in various bacteria.
Tunable DNMT1 degradation reveals cooperation of DNMT1 and DNMT3B in regulating DNA methylation dynamics and genome organization

DNA methylation (DNAme) is a key epigenetic mark that regulates critical biological processes maintaining overall genome stability. Given its pleiotropic function, studies of DNAme dynamics are crucial, but currently available tools to interfere with DNAme have limitations and major cytotoxic side effects. Here, we present untransformed and cancer cell models that allow inducible and reversible global modulation of DNAme through DNMT1 depletion. By dynamically assessing the effects of induced passive demethylation through cell divisions at both the whole genome and locus-specific level, we reveal a cooperative activity between DNMT1 and DNMT3B to maintain and control DNAme. Moreover, we show that gradual loss of DNAme is accompanied by progressive and reversible changes in heterochromatin abundance, compartmentalization, and peripheral localization. DNA methylation loss coincided with a gradual reduction of cell fitness due to G1 arrest, but with minor level of mitotic failure. Altogether, this powerful system allows DNMT and DNA methylation studies with fine temporal resolution, which may help to reveal the etiologic link between DNA methylation dysfunction and human disease.
Down-regulation of β-lactam antibiotics resistance and biofilm formation by Staphylococcus epidermidis is associated with isookanin

Introduction Biofilm formation is the major pathogenicity of Staphylococcus epidermidis (S. epidermidis), which enhances bacterial resistance to antibiotics. Isookanin has potential inhibitory activity on biofilm. Method The inhibiting mechanisms of isookanin against biofilm formation through surface hydrophobicity assay, exopolysaccharides, eDNA, gene expression analysis, microscopic visualization, and molecular docking were explored. Additionally, the combination of isookanin and β-lactam antibiotics were evaluated by the broth micro-checkerboard assay. Results The results showed that isookanin could decrease the biofilm formation of S. epidermidis by ≥85% at 250 μg/mL. The exopolysaccharides, eDNA and surface hydrophobicity were reduced after treatment with isookanin. Microscopic visualization analysis showed that there were fewer bacteria on the surface of the microscopic coverslip and the bacterial cell membrane was damaged after treatment with isookanin. The down-regulation of icaB and up-regulation of icaR were observed after treatment with isookanin. Additionally, the RNAIII gene was significantly up-regulated (p < 0.0001) at the mRNA level. Molecular docking showed that isookanin could bind to biofilm-related proteins. This indicated that isookanin can affect biofilm formation at the initial attachment phase and the aggregation phase. The FICI index showed that the combination of isookanin and β-lactam antibiotics were synergistic and could reduce doses of antibiotics by inhibiting biofilm formation. Discussion This study improved the antibiotic susceptibility of S. epidermidis through inhibition of the biofilm formation, and provided a guidance for the treatment of antibiotic resistance caused by biofilm
Fungal network composition and stability in two soils impacted by trifluralin

Introduction The composition and stability of soil fungal network are important for soil function, but the effect of trifluralin on network complexity and stability is not well understood. Methods In this study, two agricultural soils were used to test the impact of trifluralin on a fungal network. The two soils were treated with trifluralin (0, 0.84, 8.4, and 84 mg kg−1) and kept in artificial weather boxes. Results and discussion Under the impact of trifluralin, the fungal network nodes, edges, and average degrees were increased by 6–45, 134–392, and 0.169–1.468 in the two soils, respectively; however, the average path length was decreased by 0.304–0.70 in both soils. The keystone nodes were also changed in trifluralin treatments in the two soils. In the two soils, trifluralin treatments shared 219–285 nodes and 16–27 links with control treatments, and the network dissimilarity was 0.98–0.99. These results indicated that fungal network composition was significantly influenced. After trifluralin treatment, fungal network stability was increased. Specifically, the network robustness was increased by trifluralin with 0.002–0.009, and vulnerability was decreased by trifluralin with 0.0001–0.00032 in the two soils. Fungal network community functions were also impacted by trifluralin in both soils. Trifluralin significantly impacts the fungal network.
Movement patterns in tuba playing: comparison of an embouchure dystonia case with healthy professional tuba players using real-time MRI imaging

Introduction Musculoskeletal problems in professional brass musicians are very common and often involve the muscles of the embouchure. In rare cases, embouchure dystonia (EmD), a task-specific movement disorder with a wide symptomatic and phenotypic variability, occurs. Following trumpeters and horn players, professional tuba players with and without EmD have now been studied using the latest real-time MRI technology to better understand the underlying pathophysiology. Materials and methods In the present study, the tongue movement patterns of 11 healthy professional artists and one subject suffering from EmD were compared. The tongue position in the anterior, intermediary and posterior oral cavity were converted into pixel positions based on seven previously generated profile lines, using the established software MATLAB. These data allow a structured comparison of tongue movement patterns between the patient and the healthy subjects, as well as between individual exercises. The main focus of the analysis was on an ascending 7-note harmonic series performed in different playing techniques (slurred, tongued, tenuto and staccato). Results Playing the ascending harmonics, a noticeable ascending tongue movement could be observed in the anterior part of the oral cavity in healthy tubists. In the posterior region, there was a slight decrease in oral cavity space. In the EmD patient, hardly any movement was observed at the tongue apex, but in the middle and posterior regions of the oral cavity there was an increase in size the higher the tone became. These distinct differences are relevant for the characterization and a better understanding of the clinical presentation of EmD. Concerning different playing techniques, it was apparent, that notes played slurred or staccato resulted in a larger oral cavity when compared to notes played tongued or tenuto, respectively. Conclusion By using real-time MRI videos, the tongue movements of tuba players can be clearly observed and analyzed. The differences between healthy and diseased tuba players demonstrate the great effects of movement disorders in a small area of the tongue. In order to better understand the compensation of this motor control dysfunction, further studies should investigate further parameters of tone production in all brass players with a larger number of EmD patients additional to the observed movement patterns.
Employing automotive security to improve the security of unmanned aerial vehicles

The concern about cyber threats on unmanned aerial vehicles (UAVs) increases as they become more sophisticated and widely used in various areas. Although there have been efforts to improve the security of UAVs, their focus is limited to physical attacks and securing communication, and many areas remain open to issues. Although a more comprehensive approach is required to improve the overall areas of UAVs, it is reasonable to investigate the case study from the perspective of other similar cyber-physical systems (CPSs). Thus, we see the architectural similarity between UAVs and automobiles. Automotive security has seen significant improvement throughout the last decade as vehicles have begun to have connectivity and autonomy. There have been extensive research and development efforts in various aspects, including securing the components, securing communications, securing software updates, and securing the overall management system to provide multi-layered security for the automotive environments, and standardization and regulations are being issued. Due to the similarity, the employment of ideas from the automotive environments in the UAV environments becomes a reasonable approach. In this paper, we show the automotive security trends and discuss how UAV environments are comparable to automotive environments. We then show how security in automotives is adapted in UAVs with a case study.
Lipid remodeling of contrasting maize (Zea mays L.) hybrids under repeated drought

The role of recovery after drought has been proposed to play a more prominent role during the whole drought-adaption process than previously thought. Two maize hybrids with comparable growth but contrasting physiological responses were investigated using physiological, metabolic, and lipidomic tools to understand the plants’ strategies of lipid remodeling in response to repeated drought stimuli. Profound differences in adaptation between hybrids were discovered during the recovery phase, which likely gave rise to different degrees of lipid adaptability to the subsequent drought event. These differences in adaptability are visible in galactolipid metabolism and fatty acid saturation patterns during recovery and may lead to a membrane dysregulation in the sensitive maize hybrid. Moreover, the more drought-tolerant hybrid displays more changes of metabolite and lipid abundance with a higher number of differences within individual lipids, despite a lower physiological response, while the responses in the sensitive hybrid are higher in magnitude but lower in significance on the level of individual lipids and metabolites. This study suggests that lipid remodeling during recovery plays a key role in the drought response of plants.
Cyclostratigraphy and high-frequency sedimentary cycle framework for the Late Paleozoic Fengcheng Formation, Junggar Basin

The Late Paleozoic Fengcheng Formation within the Mahu Sag of the Junggar Basin (China) harbors the world’s oldest alkaline lake hydrocarbon source rocks. Spectral analysis of the natural gamma-ray (GR) series obtained from four boreholes traversing the Fengcheng Formation, with wavelength ranges of 28.4 m–50 m, 5.9 m–12.6 m, 2.3 m–3.9 m, and 1.2 m–2.7 m. These were controlled by Early Permian astronomical cycles, including 405 kyr long eccentricity, 100 kyr short eccentricity, 34.2 kyr obliquity, and 20.7–17.4 kyr precession. The most significant cycle was notably that of the 405 kyr long eccentricity, which was instrumental for dividing and correlating the high-frequency sedimentary sequences in lacustrine shales. Nine intermediate-term and 36 short-term base-level cycles were identified in the P1f1 and P1f2 members of the Fengcheng Formation. These cycle types are equal to the 405 kyr long eccentricity cycle and ∼100 kyr short eccentricity cycle, respectively. The paleolake-level variations in the Fengcheng Formation were reconstructed using sedimentary noise modeling, revealing that lake levels reached their highest value during the deposition of the P1f2 Member. The spatial distribution patterns of lithofacies in the Fengcheng Formation can be clearly demonstrated within the isochronous cycle framework under the constraints of long eccentricity cycles. The use of astronomical cycles in isochronous stratigraphic correlation offers great potential for characterizing alkaline lacustrine sequences and predicting favorable areas for shale oil exploration with higher accuracy.