Miracle-dz/UniFAR-FTUs huggingface dataset:
A deep active learning-based and crowdsourcing-assisted solution for named entity recognition in Chinese historical corpora

PurposeThe majority of existing studies about named entity recognition (NER) concentrate on the prediction enhancement of deep neural network (DNN)-based models themselves, but the issues about the scarcity of training corpus and the difficulty of annotation quality control are not fully solved, especially for Chinese ancient corpora. Therefore, designing a new integrated solution for Chinese historical NER, including automatic entity extraction and man-machine cooperative annotation, is quite valuable for improving the effectiveness of Chinese historical NER and fostering the development of low-resource information extraction.Design/methodology/approachThe research provides a systematic approach for Chinese historical NER with a three-stage framework. In addition to the stage of basic preprocessing, the authors create, retrain and yield a high-performance NER model only using limited labeled resources during the stage of augmented deep active learning (ADAL), which entails three steps—DNN-based NER modeling, hybrid pool-based sampling (HPS) based on the active learning (AL), and NER-oriented data augmentation (DA). ADAL is thought to have the capacity to maintain the performance of DNN as high as possible under the few-shot constraint. Then, to realize machine-aided quality control in crowdsourcing settings, the authors design a stage of globally-optimized automatic label consolidation (GALC). The core of GALC is a newly-designed label consolidation model called simulated annealing-based automatic label aggregation (“SA-ALC”), which incorporates the factors of worker reliability and global label estimation. The model can assure the annotation quality of those data from a crowdsourcing annotation system.FindingsExtensive experiments on two types of Chinese classical historical datasets show that the authors’ solution can effectively reduce the corpus dependency of a DNN-based NER model and alleviate the problem of label quality. Moreover, the results also show the superior performance of the authors’ pipeline approaches (i.e. HPS + DA and SA-ALC) compared to equivalent baselines in each stage.Originality/valueThe study sheds new light on the automatic extraction of Chinese historical entities in an all-technological-process integration. The solution is helpful to effectively reducing the annotation cost and controlling the labeling quality for the NER task. It can be further applied to similar tasks of information extraction and other low-resource fields in theoretical and practical ways.
Optical Light Sources and Wavelengths within the Visible and Near-Infrared Range Using Photoacoustic Effects for Biomedical Applications

The photoacoustic (PA) effect occurs when sound waves are generated by light according to the thermodynamic and optical properties of the materials; they are absorption spectroscopic techniques that can be applied to characterize materials that absorb pulse or continuous wave (CW)-modulated electromagnetic radiation. In addition, the wavelengths and properties of the incident light significantly impact the signal-to-ratio and contrast with photoacoustic signals. In this paper, we reviewed how absorption spectroscopic research results have been used in applying actual photoacoustic effects, focusing on light sources of each wavelength. In addition, the characteristics and compositions of the light sources used for the applications were investigated and organized based on the absorption spectrum of the target materials. Therefore, we expect that this study will help researchers (who desire to study photoacoustic effects) to more efficiently approach the appropriate conditions or environments for selecting the target materials and light sources.
Cooperative Roundabout Control Strategy for Connected and Autonomous Vehicles

Intersections in the urban network are potential sources of traffic flow inefficiency. Existing intersection control mostly adopts the “cross” flow pattern model, while the use of the roundabout circular flow pattern is rather sparse. Connected and autonomous vehicle (CAV) technologies can enable roundabouts to better compete with traditional intersection designs in terms of performance. This study proposes a roundabout control strategy for CAVs to enhance intersection performance while ensuring vehicle safety. A hierarchical framework is developed to decouple the flow-level performance objective and vehicle-level safety constraints to achieve computational tractability for real-time applications. It entails developing a roundabout flow control model to optimize merge-in flows, a merge-in decision model to generate vehicle passing sequence from the optimal flows, and a virtual platoon control model to achieve safe and stable vehicle operations in a circular roundabout platoon. The performance of the proposed roundabout control strategy is illustrated through numerical studies and compared to existing intersection control methods. Its stability and safety characteristics are also demonstrated.
Design of a Folded, Double-Tuned Loop Coil for ¹H/X-Nuclei MRI Applications

MR measurement using a combination of X-nuclei and proton MRI is of great interest as the information provided by the two nuclei is highly complementary, with the X-nuclei signal giving metabolic data relating to potential biomarkers and the proton signal affording anatomical details. Due to the relatively weak signal obtained from X-nuclei, combining an X-nuclei coil with a proton coil is also advantageous for <inline-formula> <tex-math notation="LaTeX">$\text{B}_{{0}}$ </tex-math></inline-formula> shimming and scout images. One approach to building a double-resonant coil is to modify the coil geometry. Here, to achieve double-resonance, a <inline-formula> <tex-math notation="LaTeX">$2\times $ </tex-math></inline-formula> 1 ladder network was designed and tuned at both proton and X-nuclei frequencies successfully. Due to coupling between closed wires, the double-tuned coil generates a shifted transmit efficiency pattern compared to that of the single-tuned loop at the 7T MRI proton frequency. To compensate for the shifted pattern, one part of the <inline-formula> <tex-math notation="LaTeX">$2\times $ </tex-math></inline-formula> 1 ladder network was folded, and the tuning and performance of the folded double-tuned coil were evaluated in simulations and MR measurements. The proposed structure was further evaluated with overlapped decoupling in a receive-only array. The results show that our proposed folded double-tuned coil moderated the shifted pattern of a straight double-tuned loop coil and provided minimum losses at both proton and X-nuclei frequencies. The proposed folded double-tuned loop coil has also been further extended to a receive-only array.
Effect of difluoromethylornithine on thyroid function in rats.

BACKGROUND A variety of stimuli cause a rapid increase in polyamine synthesis by increasing an enzyme ornithine decarboxylase required for the biosynthetic pathway of protein synthesis. Difluoromethyl ornithine is a selective inhibitor of this enzyme and hence arrests cell replication strikingly. Its effects on thyroid gland are studied with respect to change in animal's weight and levels of Triiodothyronine, Thyroxine and Thyroid stimulating hormone. The study was conducted to evaluate the inhibitory effects of Di-fluoromethyl ornithine (DFMO) administration on polyamine metabolism of thyroid gland in rats. METHODS The study was conducted on rats weighing 248 to 320 grams, divided into control and DFMO treated group. A dose of 50 mg/rat was administered subcutaneously to the treated group for 5 consecutive days and placebo (normal saline) injections to control group. On sixth day, blood was collected by cardiac puncture and serum was separated. Serum T3, T4 and TSH were analyzed with the help of radioimmunoassay in both groups. RESULTS In treated group there was a fall in T3, T4 concentration with significant rise in TSH concentration as compared to control group. CONCLUSION DFMO (Difluoro methyl ornithine) decreases cellular proliferation of thyroid gland as is assessed by decrease in thyroid hormone levels. The hypothalamo pituitary thyroid axis however remains intact as is shown by a feedback rise in TSH concentration. DFMO can thus be employed for anti-neoplastic clinical trials on account of interference with activity of ODC (Ornithine Decarboxylase) fundamental for polyamine biosynthesis.
Integrated Metabolomics and Transcriptomics Reveal Metabolic Patterns in Retina of STZ-Induced Diabetic Retinopathy Mouse Model

Diabetic retinopathy (DR), as the leading cause of vision loss in the working-age population, exhibits unique metabolite profiles in human plasma and vitreous. However, those in retina are not fully understood. Here, we utilized liquid and gas chromatography–tandem mass spectrometry technology to explore metabolite characteristics of streptozotocin (STZ)-induced diabetic mice retina. A total of 145 metabolites differed significantly in diabetic retinas compared with controls. These metabolites are mainly enriched in the Warburg effect, and valine, leucine and isoleucine degradation pathways. To further identify underlying regulators, RNA sequencing was performed to integrate metabolic enzyme alterations with metabolomics in STZ-induced diabetic retina. Retinol metabolism and tryptophan metabolism are the shared pathways enriched by metabolome and transcriptome. Additionally, transcriptomic analysis identified 71 differentially expressed enzyme-related genes including Hk2, Slc7a5, Aldh1a3 and Tph integrated with altered metabolic pathways. In addition, single nucleotide polymorphisms within 6 out of 71 genes are associated with increased diabetes risk. This study lays the foundation for mechanism research and the therapeutic target development of DR.
Psychosocial Predictors of Drop-Out from Organised Sport: A Prospective Study in Adolescent Soccer

In recent years an increased drop-out rate in adolescents’ soccer participation has been observed. Given the potentially adverse consequences of drop-out from soccer, more information about risk factors for drop-out is warranted. In the current study, Classification and Regression Tree (CRT) analysis was used to investigate demographic and motivational factors associated with an increased risk of drop-out from adolescent soccer. The results of this study indicate that older age, experiencing less autonomy support from the coach, less intrinsic motivation, being female, and lower socioeconomic status are factors associated with an increased risk of drop-out. An interpretation of the results of this study is that coaches play a central part in creating a sports context that facilitates motivation and continued soccer participation. Based on the findings of the current study we propose that soccer clubs implement theoretically informed coach education programs to help coaches adopt autonomy-supportive coaching strategies.
Opposing Actions of TLR2 and TLR4 in Adipocyte Differentiation and Mature-Onset Obesity

Understanding the signaling cascades that govern adipocyte metabolism and differentiation is necessary for the development of therapies for obesity. Toll-like receptors (TLRs) are key mediators in adipogenesis, but their specific role is not completely understood. In this study, siRNA knockdown of Tlr2 in 3T3-L1 cells allowed them to differentiate more efficiently into adipocytes, whereas the opposite was observed for the knockdown of Tlr4. At the same time, we show that TLR2 knock-out mice spontaneously developed mature-onset obesity and insulin resistance. Besides a higher incidence of hyperplasia and hypertrophy in white adipose tissue (WAT), we found a significantly increased number of adipocyte precursor cells in TLR2−/− mice compared to TLR4−/− mice. Interestingly, genetic inactivation of Tlr4 in TLR2−/− mice reverted their increased adiposity, insulin resistance, and restored normal levels of adipocyte precursor cells. These findings provide evidence that TLR2 and TLR4 play opposing roles in WAT homeostasis and point to the existence of cross-regulation among TLR2 and TLR4 during adipocyte differentiation both in vitro and in vivo.
Monoid networks and counting permutations by runs

We generalize the combinatorial framework of free monoids to what we call a "monoid network", which allows us to count words in a free monoid on an alphabet $A$ corresponding to walks between specified vertices in a digraph where each arc is assigned a subset of $A$. Our main result is a generalization of a theorem of Gessel to the monoid network setting, and we use it to complete the enumeration of permutations with parity restrictions on peaks and valleys, and to give a systematic method for obtaining generating functions for permutation statistics that can be characterized in terms of increasing runs.
A Notch Filter-Based Coupling Circuit for UNB and NB PLC Systems

This paper introduces an analog notch filtering-based coupling circuit for receivers in ultra-narrowband and narrowband power line communication systems, which are connected to low-voltage electric power grids. It is composed of a twin-T notch analog filter, which is responsible for imposing a significant attenuation on the main frequency (i.e., f0∈{50,60} Hz) in cascade with an elliptic low-pass analog filter, designed with a 3 dB cut-off frequency of fc≫f0. For f0=60 Hz and fc=2 MHz, the prototype of the analog notch filtering-based coupling circuit attains attenuation values of 22 dB and less than 2 dB at the main frequency and in the rest of the frequency bandwidth, respectively, when practical scenarios are considered. Lastly, it shows that the analog notch filtering-based coupling circuit is more effective than a typical capacitive coupling circuit when frequencies lower than 3 kHz are considered for data communication and sensing purposes.
Loss of Myostatin Alters Mitochondrial Oxidative Phosphorylation, TCA Cycle Activity, and ATP Production in Skeletal Muscle

Simple Summary Myostatin (MSTN) negatively regulates skeletal muscle growth. Although the role of MSTN in muscle hypertrophy can be investigated in depth, studies of MSTN in mitochondrial energy metabolism in muscle would be valuable. In this study, we evaluated the importance of MSTN in regulating mitochondrial energy metabolism in MSTN-knockout (Mstn−/−) mice and explored the possible mechanisms. A loss of MSTN inhibits oxidative phosphorylation, alters TCA cycle activity, and impairs ATP production in skeletal muscles. These changes may be achieved through TGF-β-Smad2/3. These results suggest that MSTN may be an important regulator of mitochondrial energy homeostasis in mice. Abstract Myostatin (MSTN) is an important negative regulator of skeletal muscle growth in animals. A lack of MSTN promotes lipolysis and glucose metabolism but inhibits oxidative phosphorylation (OXPHOS). Here, we aimed to investigate the possible mechanism of MSTN regulating the mitochondrial energy homeostasis of skeletal muscle. To this end, MSTN knockout mice were generated by the CRISPR/Cas9 technique. Expectedly, the MSTN null (Mstn−/−) mouse has a hypermuscular phenotype. The muscle metabolism of the Mstn−/− mice was detected by an enzyme-linked immunosorbent assay, indirect calorimetry, ChIP-qPCR, and RT-qPCR. The resting metabolic rate and body temperature of the Mstn−/− mice were significantly reduced. The loss of MSTN not only significantly inhibited the production of ATP by OXPHOS and decreased the activity of respiratory chain complexes, but also inhibited key rate-limiting enzymes related to the TCA cycle and significantly reduced the ratio of NADH/NAD+ in the Mstn−/− mice, which then greatly reduced the total amount of ATP. Further ChIP-qPCR results confirmed that the lack of MSTN inhibited both the TCA cycle and OXPHOS, resulting in decreased ATP production. The reason may be that Smad2/3 is not sufficiently bound to the promoter region of the rate-limiting enzymes Idh2 and Idh3a of the TCA cycle, thus affecting their transcription.
An autoethnography of automated powerlessness: lacking platform affordances in Instagram and TikTok account deletions

Situated within the field of platform governance studies, this paper shares findings from an ‘autoethnography of automated powerlessness’, drawing from the researcher’s disempowering experience of being a heavily moderated social media user. Using theoretical frameworks blending affordances and World Risk Society theories, this paper contextualises my experiences of moderation of my pole dance instructor, activist and blogger account @bloggeronpole from February to October 2021 within social media’s broader de-platforming of nudity and sexuality, finding fallacies within platforms’ own affordances, which lack mechanisms to aid or rehabilitate de-platformed accounts. With little to no information from platforms about the details of their moderation, qualitative, ethnographic and autoethnographic explorations of their governance are all users currently have to fight and understand their puritan, patriarchal censorship of nudity and sexuality, which are often conflated with risk. This study concludes with recommendations for different options for better, more equal and community focused moderation.
A Comparison of Impedance and Antenna Analyzers on the Basis of Machine Learning Assisted Limit of Detection Experiments

Impedance measurement of quartz crystal microbalance (QCM) to quantify mass adhered on the surface and/or viscoelastic properties thereof in solution is the most informative methodology among all available techniques. State of the art impedance measurement requires advanced and costly equipment. However, recent advances in digital technology lead the way for the development of battery powered antenna analyzers capable of measuring impedance at a fraction of the cost of an expensive, benchtop impedance analyzer. Machine learning (ML), or the ability of self-training computer algorithms to autonomously interpret the structure of the data enables us to learn specific patterns or trends from data in order to perform complex tasks such as prediction, classification, clustering and regression. In this study a machine learning (ML) approach allowing optimization of impedance parameters to reduce limit of detection (LOD) is used to compare the performance of 2 different battery powered antenna analyzers with a benchtop impedance analyzer, by determining the LOD of glycerol concentration in distilled water. Monitoring of the fundamental resonance peak (10 MHz) of an AT cut QCM with the ML optimized parameters determined for each instrument, revealed a ≈ 22% difference in the lowest LODs of impedance analyzer and antenna analyzers, respectively.
Prebiotic Assembly of Cloverleaf tRNA, Its Aminoacylation and the Origin of Coding, Inferred from Acceptor Stem Coding-Triplets

tRNA is a key component in life’s most fundamental process, the translation of the instructions contained in mRNA into proteins. Its role had to be executed as soon as the earliest translation emerged, but the questions of the prebiotic tRNA materialization, aminoacylation, and the origin of the coding triplets it carries are still open. Here, these questions are addressed by utilizing a distinct pattern of coding triplets highly conserved in the acceptor stems from the modern bacterial tRNAs of five early-emerging amino acids. Self-assembly of several copies of a short RNA oligonucleotide that carries a related pattern of coding triplets, via a simple and statistically feasible process, is suggested to result in a proto-tRNA model highly compatible with the cloverleaf secondary structure of the modern tRNA. Furthermore, these stem coding triplets evoke the possibility that they were involved in self-aminoacylation of proto-tRNAs prior to the emergence of the earliest synthetases, a process proposed to underlie the formation of the genetic code. Being capable of autonomous materialization and of self-aminoacylation, this verifiable model of the proto-tRNA advent adds principal components to an initial set of molecules and processes that may have led, exclusively through natural means, to the emergence of life.
Quality of Life in Hematologic Malignancy in the Eastern Mediterranean Region: A Systematic Review

Health-related quality of life (HRQoL) indicates patients’ overall health and is an essential aspect of cancer care. Although multiple studies have addressed the various aspects of HRQoL in cancer patients, few studies have investigated HRQoL in hematologic malignancy patients in the Eastern Mediterranean region (EMR). This review conducted an electronic search using OVID-Medline to identify HRQoL-related articles involving hematologic malignancy patients in the EMR. Eight studies met the inclusion criteria. Two studies validated translated QoL psychometric instruments, three were observational studies, and three were interventional studies. Except for the validation studies, all studies discussed HRQoL in leukemia patients. Our review highlighted a scarcity in the number of studies focusing on patients with hematological malignancies in this region. The included studies demonstrated the negative impact of hematological malignancies and therapies on patients’ HRQoL. In addition, the studies displayed the association between physical symptoms and QoL of cancer patients, necessitating the importance of addressing these symptoms. The studies were limited by publication year, the number of patients, geographical locations, and disease entities. Future studies in this area are encouraged to help understand factors affecting HRQoL in the EMR region and ways to improve it. Consequently, further research is needed to establish translated and validated QoL assessment instruments that target patients in the EMR using the most common tools including the Short-Form 36-item Health Survey and the European Organization for the Research and Treatment of Cancer Quality of Life Questionnaire.
Super-Haar designs of wavelet transforms

A linear superposition of Haar transform is given to design an adaptive biorthogonal subband coding. Given Haar scaling function, rect(x), a new symmetric staircase scaling function may be desirable in order to match a specific compression or recognition goal. Then, the associated lowpass filter coefficients are solved from the roots on a unit circle in the z-transform domain. From which the bi-orthogonal and lossless high pass filter is derived for both the forward analysis and the backward synthesis stages. An explicit construction of super-Haar system produces a lossless filter bank which can match an infrared image for achieving pattern recognition and compression simultaneously.