Miracle-dz/UniFAR-FTUs huggingface dataset:
Trade-Offs in Decentralized Multi-Antenna Architectures: Sparse Combining Modules for WAX Decomposition

With the increase in the number of antennas at base stations (BSs), centralized multi-antenna architectures have encountered scalability problems from excessive interconnection bandwidth to the central processing unit (CPU), as well as increased processing complexity. Thus, research efforts have been directed towards finding decentralized receiver architectures where a part of the processing is performed at the antenna end (or close to it). A recent paper put forth an information-lossless trade-off between level of decentralization (inputs to CPU) and decentralized processing complexity (multiplications per antenna). This trade-off was obtained by studying a newly defined matrix decomposition–the WAX decomposition–which is directly related to the information-lossless processing that should to be applied in a general framework to exploit the trade-off. The general framework consists of three stages: a set of decentralized filters, a linear combining module, and a processing matrix applied at the CPU; these three stages are linear transformations which can be identified with the three constituent matrices of the WAX decomposition. The previous work was unable to provide explicit constructions for linear combining modules which are valid for WAX decomposition, while it remarked the importance of these modules being sparse with 1s and 0s so they could be efficiently implemented using hardware accelerators. In this work we present a number of constructions, as well as possible variations of them, for effectively defining linear combining modules which can be used in the WAX decomposition. Furthermore, we show how these structures facilitate decentralized calculation of the WAX decomposition for applying information-lossless processing in architectures with an arbitrary level of decentralization.
Pastoralist landscapes and social interaction in bronze age Eurasia

Offering a fresh archaeological interpretation, this work reconceptualizes the Bronze Age prehistory of the vast Eurasian steppe during one of the most formative and innovative periods of human history. Michael D. Frachetti combines an analysis of newly documented archaeological sites in the Koksu River valley of eastern Kazakhstan with detailed paleoecological and ethnohistorical data to illustrate patterns in land use, settlement, burial, and rock art. His investigation illuminates the practical effect of nomadic strategies on the broader geography of social interaction and suggests a new model of local and regional interconnection in the third and second millennia B.C.E. Frachetti further argues that these early nomadic communities played a pivotal role in shaping enduring networks of exchange across Eurasia.
New and more effective application assays for hemostatic disorder assessment: A systematic review

Background: Hemostasis research lacked novel platform assays for hemostatic disorder diagnosis. The current review study’s goal is to compare various assays for evaluating the novel hemostatic techniques used in the diagnosis of coagulation disturbances and to highlight each method’s strongest and weakest points. Methods: The PRISMA guidelines and the recommendations for observational studies in epidemiology were both followed in the current systematic review. The PRISMA-compliant electronic databases (PubMed), a novel platform for evaluating hemostasis, were searched using the keywords. The electronic databases (PubMed), a cutting-edge platform to assess hemostasis, were searched using the keywords. Articles published between December 2016 and December 2021 were only included in searches; original articles were written in English. In order to assess hemostasis studies, we gathered bibliographies of abstracts that were published on the new and more effective application assays for assessments of hemostasis disorders. Results: Following the removal of duplicates, articles were determined by examining the titles and abstracts. Disagreements were resolved through consensus and the application of novel hemostatic analysis methods. Then independently reviewed the relevant studies of the recognized records (n=503), excluding duplicates (n=9) and irrelevant studies (n=249). The remaining 254 studies were read in their entirety, the data from the seven included studies had been extracted. Conclusions: When expressed as an anticoagulant for the in vivo assessment of on the complement system, nanotechnology-based study was more effective in some laboratory tests, and flow cytometer evaluation could be a promising platform approach for use in hemostasis management.
Anti-quorum sensing potential of selenium nanoparticles against LasI/R, RhlI/R, and PQS/MvfR in Pseudomonas aeruginosa: a molecular docking approach

Pseudomonas aeruginosa is an infectious pathogen which has the ability to cause primary and secondary contagions in the blood, lungs, and other body parts of immunosuppressed individuals, as well as community-acquired diseases, such as folliculitis, osteomyelitis, pneumonia, and others. This opportunistic bacterium displays drug resistance and regulates its pathogenicity via the quorum sensing (QS) mechanism, which includes the LasI/R, RhlI/R, and PQS/MvfR systems. Targeting the QS systems might be an excellent way to treat P. aeruginosa infections. Although a wide array of antibiotics, namely, newer penicillins, cephalosporins, and combination drugs are being used, the use of selenium nanoparticles (SeNPs) to cure P. aeruginosa infections is extremely rare as their mechanistic interactions are weakly understood, which results in carrying out this study. The present study demonstrates a computational approach of binding the interaction pattern between SeNPs and the QS signaling proteins in P. aeruginosa, utilizing multiple bioinformatics approaches. The computational investigation revealed that SeNPs were acutely ‘locked’ into the active region of the relevant proteins by the abundant residues in their surroundings. The PatchDock-based molecular docking analysis evidently indicated the strong and significant interaction between SeNPs and the catalytic cleft of LasI synthase (Phe105-Se = 2.7 Å and Thr121-Se = 3.8 Å), RhlI synthase (Leu102-Se = 3.7 Å and Val138-Se = 3.2 Å), transcriptional receptor protein LasR (Lys42-Se = 3.9 Å, Arg122-Se = 3.2 Å, and Glu124-Se = 3.9 Å), RhlR (Tyr43-Se = 2.9 Å, Tyr45-Se = 3.4 Å, and His61-Se = 3.5 Å), and MvfR (Leu208-Se = 3.2 Å and Arg209-Se = 4.0 Å). The production of acyl homoserine lactones (AHLs) was inhibited by the use of SeNPs, thereby preventing QS as well. Obstructing the binding affinity of transcriptional regulatory proteins may cause the suppression of LasR, RhlR, and MvfR systems to become inactive, thereby blocking the activation of QS-regulated virulence factors along with their associated gene expression. Our findings clearly showed that SeNPs have anti-QS properties against the established QS systems of P. aeruginosa, which strongly advocated that SeNPs might be a potent solution to tackle drug resistance and a viable alternative to conventional antibiotics along with being helpful in therapeutic development to cure P. aeruginosa infections.
Similarity evaluation method of single flow point energy consumption mapping based on Fréchet distance

Aiming at the problem of inaccurate measurement results caused by factors such as gas leakage during the calibration of the standard meter gas flow standard device of the same type and small diameter, this paper proposes a similarity assessment method of single flow point energy consumption mapping based on Fréchet distance (FD). First, through the statistical analysis of the historical energy consumption data of gas flow standard device, a discrete standard energy consumption mapping is formed. Next, the energy consumption mapping to be tested is standardized and the similarity of the energy consumption mapping is determined by the binary matrix accelerated search of the FD between the energy consumption mapping to be tested and the standard energy consumption mapping. Finally, the similarity threshold is calculated by combining the standard deviation of the FD and the reliability of the gas flowmeter calibration process is evaluated accordingly. The test shows that the method in this paper can effectively determine the reliability of the gas flowmeters calibration results.
Fc multimers effectively treat murine models of multiple sclerosis

Multiple Sclerosis (MS) is a chronic neurodegenerative disease with limited therapeutic options. Recombinant Fc multimers (rFc), designed to mirror many of the anti-inflammatory activities of Intravenous Immunoglobulin (IVIG), have been shown to effectively treat numerous immune-mediated diseases in rodents. In this study we used the experimental autoimmune encephalomyelitis (EAE) murine model of MS to test the efficacy of a rFc, M019, that consists of multimers of the Fc portion of IgG2, in inhibiting disease severity. We show that M019 effectively reduced clinical symptoms when given either pre- or post-symptom onset compared to vehicle treated EAE induced mice. M019 was effective in reducing symptoms in both SJL model of relapsing remitting MS as well as the B6 model of chronic disease. M019 binds to FcγR bearing-monocytes both in vivo and in vitro and prevented immune cell infiltration into the CNS of treated mice. The lack of T cell infiltration into the spinal cord was not due to a decrease in T cell priming; there was an equivalent frequency of Th17 cells in the spleens of M019 and vehicle treated EAE induced mice. Surprisingly, there was an increase in chemokines in the sera but not in the CNS of M019 treated mice compared to vehicle treated animals. We postulate that M019 interacts with a FcγR rich monocyte intermediary to prevent T cell migration into the CNS and demyelination.
Public and Healthcare Provider Receptivity toward the Retention of Dried Blood Spot Cards and Their Usage for Extended Genetic Testing in Hong Kong

Dried blood spot (DBS) cards from newborn screening (NBS) programs represent a wealth of biological data. They can be stored easily for a long time, have the potential to support medical and public health research, and have secondary usages such as quality assurance and forensics, making it the ideal candidate for bio-banking. However, worldwide policies vary with regard to the duration of storage of DBS cards and how it can be used. Recent advances in genomics have also made it possible to perform extended genetic testing on DBS cards in the newborn period to diagnose both actionable and non-actionable childhood and adult diseases. Both storage and secondary uses of DBS cards raise many ethical, clinical, and social questions. The openness of the key stakeholders, namely, parents and healthcare providers (HCPs), to store the DBS cards, and for what duration and purposes, and to extended genetic testing is largely dependent on local cultural–social-specific factors. The study objective is to assess the parents’ and HCPs’ awareness and receptivity toward DBS retention, its secondary usage, and extended genetic testing. A cross-sectional, self-administrated survey was adopted at three hospitals, out of which two were public hospitals with maternity services, between June and December 2022. In total, 452 parents and 107 HCPs completed and returned the survey. Overall, both HCPs and parents were largely knowledgeable about the potential benefits of DBS card storage for a prolonged period and its secondary uses, and they supported extended genetic testing. Knowledge gaps were found in respondents with a lower education level who did not know that a DBS card could be stored for an extended period (p < 0.001), could support scientific research (p = 0.033), and could aid public health research, and future policy implementation (p = 0.030). Main concerns with regard to DBS card storage related to potential privacy breaches and anonymity (Parents 70%, HCPs 60%). More parents, compared to HCPs, believed that storing DBS cards for secondary research does not lead to a reciprocal benefit to the child (p < 0.005). Regarding extended genetic testing, both groups were receptive and wanted to know about actionable childhood- and adult-onset diseases. More parents (four-fifths) rather than HCPs (three-fifths) were interested in learning about a variant with unknown significance (p < 0.001). Our findings report positive support from both parents and HCPs toward the extended retention of DBS cards for secondary usage and for extended genetic testing. However, more efforts to raise awareness need to be undertaken in addition to addressing the ethical concerns of both parents and HCPs to pave the way forward toward policy-making for DBS bio-banking and extended genetic testing in Hong Kong.
Windthrow damage detection in Nordic forests by 3D reconstruction of very high-resolution stereo optical satellite imagery

ABSTRACT We tested whether windthrow damage to Nordic conifer forest stands could be reliably detected as canopy height decrease between a pre-storm LiDAR (Light Detection and Ranging) digital surface model (DSM) and a photogrammetric DSM derived from a post-storm WorldView-3 stereo pair. The post-storm ground reference data consisted of field and unmanned aerial vehicle (UAV) observations of windthrow combined with no-damage areas collected by visual interpretation of the available very high resolution (VHR) satellite imagery. We trained and tested a thresholding model using canopy height change as the sole predictor. We undertook a two-step accuracy assessment by (1) running k-fold cross-validation on the ground reference dataset and examining the effect of the potential imperfections in the ground reference data, and (2) conducting rigorous accuracy assessment of the classified map of the study area using an extended set of VHR imagery. The thresholding model produced accurate windthrow maps in dense, productive forest stands with a sensitivity of 96%, specificity of 71%, and Matthews correlation coefficient (MCC) over 0.7. However, in sparse and high elevation stands, the classification accuracy was poor. Despite certain collection challenges during the winter months in the Nordic region, we consider VHR stereo satellite imagery to be a viable source of forest canopy height information and sufficiently accurate to map windthrow disturbance in forest stands of high to moderate density.
The application of traditional machine learning and deep learning techniques in mammography: a review

Breast cancer, the most prevalent malignant tumor among women, poses a significant threat to patients’ physical and mental well-being. Recent advances in early screening technology have facilitated the early detection of an increasing number of breast cancers, resulting in a substantial improvement in patients’ overall survival rates. The primary techniques used for early breast cancer diagnosis include mammography, breast ultrasound, breast MRI, and pathological examination. However, the clinical interpretation and analysis of the images produced by these technologies often involve significant labor costs and rely heavily on the expertise of clinicians, leading to inherent deviations. Consequently, artificial intelligence(AI) has emerged as a valuable technology in breast cancer diagnosis. Artificial intelligence includes Machine Learning(ML) and Deep Learning(DL). By simulating human behavior to learn from and process data, ML and DL aid in lesion localization reduce misdiagnosis rates, and improve accuracy. This narrative review provides a comprehensive review of the current research status of mammography using traditional ML and DL algorithms. It particularly highlights the latest advancements in DL methods for mammogram image analysis and offers insights into future development directions.
Circularly Polarized Single-Layer Microstrip Reflectarray Fed With a 2x2 Microstrip Patch Array

The design of a single-band singly-layered reflectarray fed by a circularly polarized 2x2 microstrip patch antenna array with corporate feeding to be used in K-band (18.7–19.2 GHz) is proposed in this paper. It is demonstrated by simulations and measurements that the axial ratio bandwidth performance of the reflectarray depends strongly on the circularly polarization purity of the feeder. Simulated and measured results revealed that the complete reflectarray exhibits good performance in terms of input impedance with -10 dB input reflection coefficient bandwidth of 19.0 %, radiation pattern with 3 dB axial ratio bandwidth of 10.55 % and 3 dB gain bandwidth of 2.64 %.
THE SIGNIFICANCE OF ISLAMIC EDUCATION INTEGRATION IN SUSTAINABLE DEVELOPMENT GOALS IN PURWOKERTO

This study aims to investigate the integration of Islamic education and Sustainable Development Goals (SDGs) in Purwokerto. The background highlights the significance of Islamic education in promoting values aligned with the SDGs, while also addressing the challenges of conservative interpretations and the need for inclusive approaches. The research aims to analyze the role of the Faculty of Education and Teacher Training in implementing SDGs through its curriculum, research activities, and community engagement. The findings reveal that the integration of Islamic education and SDGs in Purwokerto can foster a comprehensive approach to sustainable development, promoting environmental stewardship, social justice, and economic equity. The discussion emphasizes the importance of inclusive interpretations, curriculum development, and partnerships with various stakeholders. In conclusion, the study emphasizes the potential of Islamic education as a transformative force in achieving the SDGs in Purwokerto, while calling for ongoing efforts to address challenges and maximize the positive impact of integration.
Integrated Geophysical Investigation of Preferential Flow Paths at the Former Tyson Valley Powder Farm near Eureka, Missouri, May 2006

The U.S. Geological Survey, in cooperation with the U.S. Army Corps of Engineers, conducted surface and borehole geophysical surveys at the former Tyson Valley Powder Farm (TVPF) near Eureka, MO, to map preferential pathways on the bedrock surface for potential contaminant transport. The TVPF was formerly used as a munitions storage and disposal facility in the 1940’s and 1950’s, and the site at which the surveys were performed was a disposal area for munitions and waste solvents such as trichloroethylene (TCE) and dichloroethylene (DCE). Direct current (dc) resistivity and seismic refraction lines were acquired on the surface, and gamma, electromagnetic induction, and full waveform sonic logs were acquired in accessible boreholes. Through the combined interpretation of the seismic refraction tomographic and dc resistivity inversion results, inconsistencies in the bedrock surface were identified that may provide horizontal preferential flowpaths for dense nonaqueous phase liquid contaminants. These results, interpreted and displayed in georeferenced three-dimensional space, should help to establish more effective monitoring and remediation strategies.
Endangered by Sprawl. How Runaway Development Threatens America's Wildlife

This publication describes how, over the next half century, up to one third of the world’s plant and animal species may be lost forever because of development. Conservation biologists regard this as the first mass extinction since the age of the dinosaurs. In the United States alone, thirty percent of the nation’s plant and animal species are at risk of disappearing, and over 500 species are missing or may already be extinct. For an estimated 85 percent of these imperiled species, the loss or degradation of their habitats is the principal threat to their continued existence. The conversion of natural areas for homes, offices, and shopping centers has become one of the most serious threats to America’s native plant and animal species. Indeed, by some estimates the amount of land covered by urban and suburban development has increased by nearly 300 percent since 1955 while population has increased by only 75 percent. Furthermore, the pace of land development has been accelerating in each successive decade since the 1950s. As suburban development continues to sprawl outward, habitat loss and degradation are also likely to accelerate. This report estimates the pace of land consumption in the country’s fastest growing large metro areas over the next 25 years, and investigates what those metropolitan areas are doing to protect their natural lands from overdevelopment. In this report, we sometimes refer to natural lands as “green infrastructure” because it carries the implicit message that these open spaces are necessities that play important functional roles (e.g. filtration of water, wildlife habitat, etc.,) and thus are deserving of serious public planning and investment.
Uncovering Customer Issues through Topological Natural Language Analysis

E-commerce companies deal with a high volume of customer service requests daily. While a simple annotation system is often used to summarize the topics of customer contacts, thoroughly exploring each specific issue can be challenging. This presents a critical concern, especially during an emerging outbreak where companies must quickly identify and address specific issues. To tackle this challenge, we propose a novel machine learning algorithm that leverages natural language techniques and topological data analysis to monitor emerging and trending customer issues. Our approach involves an end-to-end deep learning framework that simultaneously tags the primary question sentence of each customer's transcript and generates sentence embedding vectors. We then whiten the embedding vectors and use them to construct an undirected graph. From there, we define trending and emerging issues based on the topological properties of each transcript. We have validated our results through various methods and found that they are highly consistent with news sources.
Degradation-Aware Dynamic Fourier-Based Network for Spectral Compressive Imaging

We consider the problem of hyperspectral image (HSI) reconstruction, which aims to recover 3D hyperspectral data from 2D compressive HSI measurements acquired by a coded aperture snapshot spectral imaging (CASSI) system. Existing deep learning methods have achieved acceptable results in HSI reconstruction. However, these methods did not consider the imaging system degradation pattern. In this article, based on observing the initialized HSIs obtained by shifting and splitting the measurements, we propose a dynamic Fourier network based on degradation learning, called the degradation-aware dynamic Fourier-based network (DADF-Net). We estimate the degradation feature maps from the degraded hyperspectral images to realize the linear transformation and dynamic processing of the features. In particular, we use the Fourier transform to extract the HSI non-local features. Extensive experimental results show that the proposed model outperforms state-of-the-art algorithms on simulation and real-world HSI datasets.
Sources and Information Reliability Measures

More and more information is shared on the web or on social media platforms, and the information provided can be conflicting. In this case, we need to decide which information is reliable and should be taken into account. We want to define measures of reliability for each source that provides information, but also to find the truth among the conflicting information, and propose properties of these measures.