Miracle-dz/UniFAR-FTUs huggingface dataset:
Historical tsunamis of Taiwan in the 18th century: the 1781 Jiateng Harbor flooding and 1782 tsunami event

Abstract. This research aims to study two historical tsunamis that occurred in Taiwan during the 18th century and to reconstruct the incidents. The 1781 Jiateng Harbor flooding, recorded by the Chinese historical document entitled “Taiwan Interview Catalogue” took place on the southwest coast of Taiwan. In contrast, the 1782 tsunami was documented in foreign languages, with uncertainties about the actual time. These two events seem to be close enough in time and location that, to some researchers, they are considered as the same event. Reasoning these historical events requires carefully examining the literature records and performing the scenarios that match the descriptions. The impact intensity analysis (IIA) is employed to locate possible regions of tsunami sources in order to reproduce the events. Numerical simulations based on the Cornell Multi-grid Coupled Tsunami Model (COMCOT) analyze the influence of different types of tsunamis generated by both submarine mass failures and seismic activities. Numerical results indicate that the source of the 1781 Jiateng Harbor flooding is located very possibly on the south-southwestern side of Taiwan. However, simulation results and historical records put the existence of the 1782 tsunami in doubt, and the possibility of storm surges could not be ruled out.
Finite time adaptive neural tracking control for non-strict-feedback uncertain non-linear systems with disturbance and input delay

In this paper, based on neural networks (NNs), we consider finite time adaptive tracking control scheme for non-strict-feedback uncertain non-linear systems with time-variant external disturbance and input delay. A novel auxiliary system has been introduced to degrade the design difficulty caused by input delay. For the unknown non-linear functions and uncertainties in each step, radial basis function NNs are introduced to approximate them such that the control objective can be obtained. Furthermore, based on the idea of backstepping technique, an effective finite time adaptive neural tracking controller has been obtained in the presence of finite time Lyapunov theory, and the singularity problem that may occur in the design process has been overcome using the piecewise functions method. Using the Lyapunov stability theorem, which shows that all the signals of the closed-loop systems are finite time bounded, and the tracking error fluctuates around the origin. Consequently, the proposed scheme not only solves the tracking problem of non-strict-feedback systems with input delay but also realizes the finite time stability performance constraint. Finally, the simulations of two examples show the superiority of the proposed scheme.
Personal Hygiene as a Risk Factors of Helminthiasis Among Primary School Students in Asia and Africa: A Literature Review

Introduction: Helminthiasis becomes one of the infectious diseases included in neglected diseases that receive less attention and mostly occurred in tropical countries. The World Health Organization (WHO) in 2020 stated that helminthiasis spread throughout sub-Saharan Africa, America, China, and East Asia where 60% suffered by children. STH infections may result from poor hygiene in many school aged-children, especially in primary school. This article was written to analyze the personal hygiene of primary school children that may affect the incidence of helminthiasis. Discussion: An integrative literature review was conducted using databases, from Google Scholar, Pubmed, Research Gate, and Science Direct databases. It was 24 articles consisting of 20 articles published by international journals and 4 articles in Indonesian journals. Most of the infectious agents in Asia were Ascaris lumbricoides and Trichuris trichiura, while Ascaris lumbricoides, Hookworms, and Trichuris trichiura dominate in Africa. Poor personal hygiene may a risk of infection. For example, children in Asia do not cut their nails or wash their hands. While children in Africa do not wash their hands, walked barefoot, and conducted open defecation. Conclusion: Personal hygiene of primary school children has a positive effect on the incidence of helminthiasis in Asia and Africa with different prevalences. To prevent and control helminthiasis in school children, schools should provide education about personal hygiene, improve sanitary facilities, and routinely give anthelmintics every six months.
Current Status of Internet Gaming Disorder (IGD) in Japan: New Lifestyle-Related Disease in Children and Adolescents

The World Health Organization recognizes internet gaming disorder (IGD) as a disorder that causes problems in daily life as a result of excessive interest in online games. The causes of IGD have become more apparent in recent years. Because of prolonged exposure to games, the mechanisms controlling the reward system, such as the prefrontal cortex, limbic system, and amygdala of the cerebrum, do not function properly in IGD. This mechanism is similar to that of various behavioral addictions, such as gambling addiction. IGD is particularly risky in children and adolescents because it easily causes brain dysfunction, especially in the developing brain. IGD should be regarded as a new lifestyle-related disease in younger individuals, and lifestyle modifications, including counseling and family therapy, are critical for its management.
Al-Ma'tsurat therapy to increase the gratitude of mothers who accompany children in distance learning

Penelitian ini bertujuan untuk mengetahui pengaruh terapi Dzikir Al- Ma’tsurat pada Ibu yang mengalami Stres Pengasuhan selama mendampingi anaknya dalam Pembelajaran Jarak Jauh (PJJ). Partisipan dari penelitian adalah ibu-ibu berjumlah 32 orang yang didapat dengan teknik purposive sampling. Metode pelaksanaan yang diterapkan adalah metode eksperimen kuasi dengan model penelitian menggunakan one group pre-test and post-test. Alat ukur yang digunakan yaitu Skala Kebersyukuran (20 aitem, α= 0,830), dan Skala Stres Pengasuhan Parental Stress Scale, (18 aitem, α=0,855). Partisipan diberikan intervensi yaitu pemberian materi mengenai pentingnya dzikir secara luring, dan pembacaan dzikir Al-Ma’tsurat selama 7 hari berturut-turut, pagi dan petang. Hasil uji analisis yang dilakukan menggunakan uji non-parametrik (wilcoxon) Statistical Package for the Social Sciences (SPSS) versi 22 pada variabel Kebersyukuran nilai Asymp. Sig. (2-tailed) = 0,164. Pada variabel Stres Pengasuhan, nilai Asymp. Sig. (2-tailed) = 0,309. Dapat disimpulkan bahwa Asymp. Sig. (2-tailed) > 0,05, sehingga tidak ada perbedaan signifikan antara nilai pre-test dan nilai post test pada variabel Kebersyukuran dan variabel Stres Pengasuhan. Saran untuk peneliti selanjutnya untuk memperhatikan karakteristik subjek penelitian secara spesifik.
Ameliorative efficacy of polyherbal formulation in streptozotocin induced diabetic rats

The aim of the present study was to determine the anti-diabetic activity of a polyherbal formulation in streptozotocin induced diabetic rats. The methanolic extracts of Achyranthes aspera, Catharanthus roseus and Momordica charantia were used in 3:1:1 w/w/w ratio for polyherbal formulation (PHF) preparation. Fifty Sprague-Dawley rats were randomly divided into five groups (GI, GII, GIII, T1 and T2) based on body weight. The high fat diet treated rats of four groups (GII, GIII, T1 and T2) were injected with 45 mg/kg body weight of streptozotocin intra peritoneally to induce diabetes. Rats of group GI, GII were kept as normal and diabetic control respectively and GIII as standard control, were administrated with glibenclamide (2.5 mg/kg, orally for 60 days); and group T1 and T2 were administered with PHF daily at a dose of 375 mg/kg and 750 mg/kg body weight respectively for a period of 60 days. Administration of PHF showed dose dependent reduction in the blood glucose level on 30th and 60th days, which was comparable to that of standard drug glibenclamide. Significant decrease in body weight and increase in serum glucose level were observed in diabetic control, which was partially restored upon administration of PHF. Altered biochemical enzymes like AST, ALT and antioxidant enzymes (SOD) were normalized by administration of PHF in diabetic rats. Also, mean values of total cholesterol, triglyceride, HDLcholesterol and LDL-cholesterol in rats treated with PHF were restored. The study indicated that PHF at higher dose showed significant decline (p<0.001) in blood glucose level.
Alleviating Al-Qur'an Illiteracy in Public Universities: A Case Study of the Al-Qur'an Reading Guidance Program at Universitas Negeri Malang

The competence of reading the holy book correctly and adequately is the obligation of every religious person. Ironically, many Muslim students do not have adequate skills in reading the Qur'an. Therefore, Universitas Negeri Malang (UM) launched a campaign to be free of Qur'an illiteracy for its students. This study aims to describe the planning, implementation, evaluation, and effectiveness of Qur'an learning at UM and the correlation of Arabic language skills to the ability to read the al-Qur'an. The method used is a mixed-method with an exploratory sequential design. The quantitative data analysis technique used normality test, Wilcoxon signed ranks, d-effect size, and calculation of N-gain value. The results of the study are as follows: (1) learning planning is carried out in a centralized and detailed manner; (2) the implementation of learning adapts to class groupings, and learning steps specified in the Qur'an Reading Guidance curriculum; (3) evaluation of learning is carried out using tashih techniques, post-test, and assessment of learning attitudes; (4) learning effectiveness is in the high category, which is indicated by the d-effect size value of 0.76, and (5) Arabic language ability is found to have a significant correlation with the ability to read the Qur'an. In general, UM is considered successful in reducing the level of Qur'an illiteracy among students.
The main driver of soil organic carbon differs greatly between topsoil and subsoil in a grazing steppe

Abstract Soil organic carbon (SOC) dynamics is regulated by a complex interplay of factors such as climate and potential anthropogenic activities. Livestocks play a key role in regulating the C cycle in grasslands. However, the interrelationship between SOC and these drivers remains unclear at different soil layers, and their potential relationships network have rarely been quantitatively assessed. Here, we completed a six‐year manipulation experiment of grazing exclusion (no grazing: NG) and increasing grazing intensity (light grazing: LG, medium grazing: MG, heavy grazing: HG). We tested light fraction organic carbon (LFOC) and heavy fraction organic carbon (HFOC) in 12 plots along grazing intensity in three soil layers (topsoil: 0–10 cm, mid‐soil: 10–30 cm, subsoil: 30–50 cm) to assess the drivers of SOC. Grazing significantly reduced SOC of the soil profile, but with significant depth and time dependencies. (1) SOC and SOC stability of the topsoil is primarily regulated by grazing duration (years). Specifically, grazing duration and grazing intensity increased the SOC lability of topsoil due to an increase in LFOC. (2) Grazing intensity was the major factor affecting the mid‐soil SOC dynamics, among which MG had significantly lower SOC than did NG. (3) Subsoil organic carbon dynamics were mainly regulated by climatic factors. The increase in mean annual temperature (MAT) may have promoted the turnover of LFOC to HFOC in the subsoil. Synthesis and applications. When evaluating the impacts of grazing on soil organic fraction, we need to consider the differences in sampling depth and the duration of grazing years. Our results highlight that the key factors influencing SOC dynamics differ among soil layers. Climatic and grazing factors have different roles in determining SOC in each soil layer.
Diffusional and antimicrobial behaviors of some antimicrobial agents in active multilayer plastic films

In this study, diffusional and antimicrobial properties of the active‐multilayer plastic films (LDPE/polyamide/LDPE‐2% antimicrobial agent) were assessed. To understand the diffusion of antimicrobials from the active plastic films containing nisin, potassium sorbate, silver substituted zeolite, or chitosan, the active‐multilayer plastic films has been put in different food simulating solutions. The food simulating solutions had various pH (3.0–7.0) and water activity (0.65–0.95) levels and were incubated at various storage temperatures (5–25°C). The release experiments for the combinations of the factors were set according to three factors face‐centered central composite design (CCF) of the response surface methodology (RSM). The diffusion rate constant (D) was calculated using Fick's law approach. The D of nisin and silver substituted zeolite was affected by pH or temperature, while aw is not a significant factor. However, Dps was found to be the highest and depended on all factors (4.45–10.04 × 10−14 cm2/s). Furthermore, no chitosan release was detected from the film matrix. The antimicrobial effectiveness of the films against microorganisms that were Staphylococcus aureus, Escherichia coli, Candida albicans, and Aspergillus niger varied according to the film type, which was verified by a challenge test on the kaşar cheese surface. Moreover, nisin and silver substituted zeolite incorporated films showed great potential to inhibit bacteria, yeast, and molds. All active films, which were studied, had featured tasks for being active food packaging material and diffused in allowance limits.
Deformations of ruled surfaces.

This paper grew out of an investigation of irreducible components of the moduli spaces of surfaces of general type. While studying surfaces with a fibration by curves of genus two which are coverings of ruled surfaces, I found to my surprise that deformations of ruled surfaces over a curve of genus greater than one have never been studied, even though ruled surfaces themselves have been the object of many papers in algebraic geometry during the last hundred years, and the cases of rational ruled surfaces [Hirz] and ruled surfaces over an elliptic curve [Suwa] showed that interesting effects related to the nonexistence of a Hausdorff moduli space do occur.
Dynamic supply chain design: a Delphi study of drivers and barriers

Supply chain management has both in academia and practice proven its important role to sustain and further develop companies’ competitive advantages. This is with initiatives that focus on cost-efficiencies and turnover improvement. During the last two decades, companies have faced complexity in their supply chains currently with increased global operations. The dynamic business environment forces companies to secure a competitive (re-) design of their supply chains. This paper seeks to advance the understanding on the drivers and barriers for such designs. In total, 39 experts (30 from industrial enterprises, 4 senior supply chain consultants and 5 supply chain management professors) have participated in a four-step Delphi study and have identified main drivers for dynamic supply chain design as being cost reduction, delivery reliability and change in demand for agility. The main barriers are identified as forecasting being too weak, supply chain complexity and product portfolio complexity. In addition, an explorative factor analysis has been carried out to identify how drivers and barriers can be grouped together. Finally, the paper compares the drivers and barriers underlining different competitive strategies.
Galois' theory of algebraic equations

Galois' Theory of Algebraic Equations gives a detailed account of the development of the theory of algebraic equations, from its origins in ancient times to its completion by Galois in the nineteenth century. The main emphasis is placed on equations of at least the third degree, i.e. on the developments during the period from the sixteenth to the nineteenth century. The appropriate parts of works by Cardano, Lagrange, Vandermonde, Gauss, Abel and Galois are reviewed and placed in their historical perspective, with the aim of conveying to the reader a sense of the way in which the theory of algebraic equations has evolved and has led to such basic mathematical notions as quot;groupquot; and quot;fieldquot;. A brief discussion on the fundamental theorems of modern Galois theory is included. Complete proofs of the quoted results are provided, but the material has been organized in such a way that the most technical details can be skipped by readers who are interested primarily in a broad survey of the theory. This book will appeal to both undergraduate and graduate students in mathematics and the history of science, and also to teachers and mathematicians who wish to obtain a historical perspective of the field. The text has been designed to be self-contained, but some familiarity with basic mathematical structures and with some elementary notions of linear algebra is desirable for a good understanding of the technical discussions in the later chapters.
Sufficient and Necessary Condition of the Lp-Brunn-Minkowski Inequality Conjecture for p\in[0,1)

A bstract . The L p − Brunn-Minkowski inequality plays a central role in the Brunn-Minkowski theory proposed by Firey [13] in 60’s and devel-oped by Lutwak [26, 27] in 90’s, which generalizes the classical Brunn-Minkowski inequality by L p − sum of convex bodies. The inequality has been established by Firey for p > 1 and later been conjectured by B¨or¨oczky-Lutwak-Yang-Zhang [5] for p ∈ [0 , 1). (see also [23, 7]) The validity of this conjecture was veriﬁed for the planar case in [5], and for the higher dimensional case when p closing to 1 by Chen-Huang-Li-Liu [7](see also a local version by Kolesnikov-Milman [23]). In this short note, we give a simple argument clarifying the equivalence between the full conjecture and a lower bound of the third eigenvalue of the Aleksandrov’s problem.
Power of Quantum Generative Learning

The intrinsic probabilistic nature of quantum mechanics invokes endeavors of designing quantum generative learning models (QGLMs). Despite the empirical achievements, the foundations and the potential advantages of QGLMs remain largely obscure. To narrow this knowledge gap, here we explore the generalization property of QGLMs, the capability to extend the model from learned to unknown data. We consider two prototypical QGLMs, quantum circuit Born machines and quantum generative adversarial networks, and explicitly give their generalization bounds. The result identifies superiorities of QGLMs over classical methods when quantum devices can directly access the target distribution and quantum kernels are employed. We further employ these generalization bounds to exhibit potential advantages in quantum state preparation and Hamiltonian learning. Numerical results of QGLMs in loading Gaussian distribution and estimating ground states of parameterized Hamiltonians accord with the theoretical analysis. Our work opens the avenue for quantitatively understanding the power of quantum generative learning models.
Self-heating of cryogenic high electron-mobility transistor amplifiers and the limits of microwave noise performance

The fundamental limits of the microwave noise performance of high electron-mobility transistors (HEMTs) are of scientific and practical interest for applications in radio astronomy and quantum computing. Self-heating at cryogenic temperatures has been reported to be a limiting mechanism for the noise, but cryogenic cooling strategies to mitigate it, for instance, using liquid cryogens, have not been evaluated. Here, we report microwave noise measurements of a packaged two-stage amplifier with GaAs metamorphic HEMTs immersed in normal and superfluid [Formula: see text]He baths and in vacuum from 1.6 to 80 K. We find that these liquid cryogens are unable to mitigate the thermal noise associated with self-heating. Considering this finding, we examine the implications for the lower bounds of cryogenic noise performance in HEMTs. Our analysis supports the general design principle for cryogenic HEMTs of maximizing gain at the lowest possible power.
Asymptotic behavior of nonexpansive sequences and mean points

Let E be a real Banach space with norm k (cid:1) k and let f x n g n (cid:21) 0 be a nonexpansive sequence in E (i.e., k x i +1 − x j +1 k (cid:20) k x i − x j k for all i; j (cid:21) 0). Let K = T 1 n =1 co ff x i − x i − 1 g i (cid:21) n g . We deal with the mean point of f x n n g concerning a Banach limit. We show that if E is reﬂexive and d = d (0 ; K ), then d = d (0 ;co f x n − x 0 n g ) and there exists a unique point z 0 with k z 0 k = d such that z 0 2 co f x n − x 0 n g . This result is applied to obtain the weak and strong convergence of f x n n g .
Branch-Train-Merge: Embarrassingly Parallel Training of Expert Language Models

We present Branch-Train-Merge (BTM), a communication-efficient algorithm for embarrassingly parallel training of large language models (LLMs). We show it is possible to independently train subparts of a new class of LLMs on different subsets of the data, eliminating the massive multi-node synchronization currently required to train LLMs. BTM learns a set of independent expert LMs (ELMs), each specialized to a different textual domain, such as scientific or legal text. These ELMs can be added and removed to update data coverage, ensembled to generalize to new domains, or averaged to collapse back to a single LM for efficient inference. New ELMs are learned by branching from (mixtures of) ELMs in the current set, further training the parameters on data for the new domain, and then merging the resulting model back into the set for future use. Experiments show that BTM improves in- and out-of-domain perplexities as compared to GPT-style Transformer LMs, when controlling for training cost. Through extensive analysis, we show that these results are robust to different ELM initialization schemes, but require expert domain specialization; LM ensembles with random data splits do not perform well. We also present a study of scaling BTM into a new corpus of 64 domains (192B whitespace-separated tokens in total); the resulting LM (22.4B total parameters) performs as well as a Transformer LM trained with 2.5 times more compute. These gains grow with the number of domains, suggesting more aggressive parallelism could be used to efficiently train larger models in future work.
Exploring Resolution and Degradation Clues as Self-supervised Signal for Low Quality Object Detection

Image restoration algorithms such as super resolution (SR) are indispensable pre-processing modules for object detection in low quality images. Most of these algorithms assume the degradation is fixed and known a priori. However, in practical, either the real degradation or optimal up-sampling ratio rate is unknown or differs from assumption, leading to a deteriorating performance for both the pre-processing module and the consequent high-level task such as object detection. Here, we propose a novel self-supervised framework to detect objects in degraded low resolution images. We utilizes the downsampling degradation as a kind of transformation for self-supervised signals to explore the equivariant representation against various resolutions and other degradation conditions. The Auto Encoding Resolution in Self-supervision (AERIS) framework could further take the advantage of advanced SR architectures with an arbitrary resolution restoring decoder to reconstruct the original correspondence from the degraded input image. Both the representation learning and object detection are optimized jointly in an end-to-end training fashion. The generic AERIS framework could be implemented on various mainstream object detection architectures with different backbones. The extensive experiments show that our methods has achieved superior performance compared with existing methods when facing variant degradation situations. Code would be released at https://github.com/cuiziteng/ECCV_AERIS.