Miracle-dz/UniFAR-FTUs huggingface dataset:
Difference in the Effect of Giving Neck Stabilization Exercise with Stretching on Improvement of Neck Functional Ability in Non-Specific Neck Pain

Background: Tailor workers when working with a bowed position and a long static position, the muscles will contract excessively resulting in spasms and pain that causes non-specific neck pain which will interfere with the functional ability of the neck. Neck stabilization exercises and stretching can be exercises to improve neck functional ability in non-specific neck pain. This study aims to determine the difference in the effect of neck stabilization exercise and stretching on increasing the functional ability of the neck in non-specific neck pain. Subjects and Method: This study is a randomized controlled trial using a two-group pretest and post-test design conducted at sevinta convection and padi emas from November to December 2023. A total of 24 subjects were selected by random sampling and randomly allocated into 2 groups. Group 1 was given neck stabilization exercise and group 2 was given stretching. The dependent variable is neck functional ability in non-specific neck pain and the independent variables are neck stabilization exercise and stretching. The measuring instrument used is the neck disability index to measure neck functional ability. Data analysis using independent sample t-test. Results: The results after the intervention obtained neck functional ability in non-specific neck pain increased in both groups. There is a statistically significant difference in neck stabilization exercise (Mean = 4.00; SD = 2.21) and stretching (Mean = 6.83; SD = 2.79), and it was statistically significant (p = 0.012). Conclusion: There is a significant difference in the effect of neck stabilization exercise and stretching on improving neck functional ability in non-specific neck pain. Neck stabilization exercise is more influential than stretching on improving neck functional ability in non-specific neck pain. Keywords: neck stabilization exercise, stretching, neck disability index. Correspondence: Yulianto Wahyono, School of Health Polytechnics Ministry of Health Surakarta. Jl. Adi Sumarmo, Tohudan, Colomadu, Karanganyar 57173, Central Java, Indonesia. Email: yulianto2wahyono@gmail.com. Mobile: 085742017903. Indonesian Journal of Medicine (2023), 08(03): 258-265
The Content of Live Microbial Biomass in the Soil in Case of Various Crops on the Example of the Farm in Starza

As it is well known, the share of microorganisms in the fertility and soil health is very important. Soil microorganisms play a major role in organic matter mineralization, provide nutrients to plants, and improve the soil structure. The size of the soil organisms is very variable. It depends primarily on the water and air relations in the soil as well as the temperature. The aim of the research was to determine the content of live microorganisms biomass in the soil under rape, maize, bean and wheat crops including the rhizosphere. The analyzes were carried out in different vegetation periods and phases of plant development on the example of the farm in Starza. Determination of living microorganisms biomass was carried out applying the method developed by Anderson and Domsch. The biomass content of live microorganisms in the soil was dependent on the cultivated plant, growing date and phase, as well as the proximity of the rhizosphere.
Seafloor Displacement After the 2011 Tohoku‐oki Earthquake in the Northern Japan Trench Examined by Repeated Bathymetric Surveys

We conducted multibeam bathymetric surveys crossing the northern Japan Trench offshore Sanriku and examined seafloor displacement by means of the difference in bathymetry before and after the 11 March 2011 Tohoku‐oki earthquake. The seafloor displacements were less than several meters in vertical displacement and less than 20 m in trench‐normal horizontal displacement; consequently, lower amplitude seafloor displacements were evaluated. Comparatively, the landward lower slope near the trench was uplifted, the middle slope was subsided, and the midslope terrace was depressed after the earthquake. Therefore, localized very large fault slip or very large submarine landslide is unlikely. Instead, smaller uplift of the lower slope near the trench extending broader along the trench seems to be plausible explanation for the devastating tsunami source in the northern Japan Trench area.
Evolutionary psychology

The Springer Series in Evolutionary Psychology is the first series of volumes dedicated to this increasingly important discipline within psychology. The series will reflect the multidisciplinary nature of this field encompassing evolutionary theory, biology, cognitive psychology, anthropology, economics, computer science, and paleoarchaeology. It will explore the underlying psychological mechanisms, and information processing systems housed in the brain as well as the various triggers for their activation. Its scientific assumptions rest on The concept that evolution is the only known causal process capable of creating complex organic mechanisms as are exhibited in human and animal life. Further, it seeks to show how information processing is adaptively influenced by input from the environment. Overall, the series will address the range of functionally specialized evolved mechanisms, mediated by contextual circumstances, that become combined and integrated to produce manifest behavior. The Series will address key areas of research within the field, including sexual behavior; conflict between the sexes; parenting; kinship; cooperation and altruism; aggression; warfare; and status and prestige. A premier resource in evolutionary psychology for researchers, academics and students, this series will provide. the field continuing and comprehensive coverage of this high profile area.
Genetic algorithms for terrain categorization of Landsat images

We have developed a method that uses genetic algorithms (GAs) to optimize rules for categorizing the terrain in Landsat data. A rule has two parts: a left side (the 'if' clause) and a right side (the 'then' clause). When the 'if' clause is true, the functions in the 'then' clause are executed to process the Landsat data. Examples of functions for processing the data include pixel by pixel threshold and a linear combination of six bands. Optimized rules are used to identify different terrain categories within Landsat data. Optimization is performed by comparing the results of the rules with ground truth using an objective function which minimizes the number of false positive and false negative pixel labels. Those rules that generate results close to the ground truth (those rules that return a small number of false positive and false negative pixel identifications) are highly rewarded and are used to create the next generation of rules. High altitude photographs were used as ground truth. The GA produced promising results for terrain categorization when compared with results from a maximum likelihood classifier. More work in the area of terrain categroization is planned to build on these promising results.
Resolving power: A general approach to compare the distinguishing ability of threshold-free evaluation metrics

Selecting an evaluation metric is fundamental to model development, but uncertainty remains about when certain metrics are preferable and why. This paper introduces the concept of resolving power to describe the ability of an evaluation metric to distinguish between binary classifiers of similar quality. This ability depends on two attributes: 1. The metric's response to improvements in classifier quality (its signal), and 2. The metric's sampling variability (its noise). The paper defines resolving power generically as a metric's sampling uncertainty scaled by its signal. The primary application of resolving power is to assess threshold-free evaluation metrics, such as the area under the receiver operating characteristic curve (AUROC) and the area under the precision-recall curve (AUPRC). A simulation study compares the AUROC and the AUPRC in a variety of contexts. It finds that the AUROC generally has greater resolving power, but that the AUPRC is better when searching among high-quality classifiers applied to low prevalence outcomes. The paper concludes by proposing an empirical method to estimate resolving power that can be applied to any dataset and any initial classification model.
Questioning whether seasonal advance of intense tropical cyclones since the 1980s truly exists

Shan et al. (2023) recently reported significant seasonal advances of intense tropical cyclones (TCs) in both the Northern Hemisphere (NH) and Southern Hemisphere (SH) since the 1980s and emphasized the data insensitivity of this conclusion, based on the advanced Dvorak Technique-Hurricane Satellite (ADT-HURSAT) and the International Best Track Archive for Climate Stewardship (IBTrACS) datasets. However, upon rigorously repeating the analysis procedure in Shan et al. (2023), we are unable to replicate their conclusion. Our analyses reveal that insignificant trends in median of intense TC occurrence dates (hereafter referred to as $\tilde{date}_{intenseTC}$) are observed in the SH based on the ADT-HURSAT, and in both hemispheres based on the IBTrACS. In addition, we discover inconsistencies in $\tilde{date}_{intenseTC}$ trends between the two datasets, which primarily arise from the differences in identification of intense TC cases. The above discrepancies raise doubts about the reproducibility and validity of Shan et al.'s conclusions regarding the seasonal advance of intense TCs. Based on these findings, as well as the limitations of both datasets, we argue that the reported seasonal advance of intense TCs since the 1980s is inconclusive and further investigations with alternative datasets and approaches are needed.
Critical slowing of the spin and charge density wave order in thin film Cr following photoexcitation

We report on the evolution of the charge density wave (CDW) and spin density wave (SDW) order of a chromium film following photoexcitation with an ultrafast optical laser pulse. The CDW is measured by ultrafast time-resolved x-ray diffraction of the CDW satellite that tracks the suppression and recovery of the CDW following photoexcitation. We find that as the temperature of the film approaches a discontinuous phase transition in the CDW and SDW order, the time scales of recovery increase exponentially from the expected thermal time scales. We extend a Landau model for SDW systems to account for this critical slowing with the appropriate boundary conditions imposed by the geometry of the thin film system. This model allows us to assess the energy barrier between available CDW/SDW states with different spatial periodicities.
A Novel Quantum Algorithm for Ant Colony Optimization

Quantum ant colony optimization (QACO) has drew much attention since it combines the advantages of quantum computing and ant colony optimization (ACO) algorithms and overcomes some limitations of the traditional ACO algorithm. However, due to the hardware resource limitations of currently available quantum computers, such as the limited number of qubits, lack of high-fidelity gating operation, and low noisy tolerance, the practical application of the QACO is quite challenging. In this paper, we introduce a hybrid quantum-classical algorithm by combining the clustering algorithm with QACO algorithm, so that this extended QACO can handle large-scale optimization problems, which makes the practical application of QACO based on available quantum computation resource possible. To verify the effectiveness and performance of the algorithm, we tested the developed QACO algorithm with the Travelling Salesman Problem (TSP) as benchmarks. The developed QACO algorithm shows better performance under multiple data set. In addition, the developed QACO algorithm also manifests the robustness to noise of calculation process, which is typically a major barrier for practical application of quantum computers. Our work shows that the combination of the clustering algorithm with QACO has effectively extended the application scenario of QACO in current NISQ era of quantum computing.
Volatility-based strategy on Chinese equity index ETF options

This study examines the performance of a volatility-based strategy using Chinese equity index ETF options. Initially successful, the strategy's effectiveness waned post-2018. By integrating GARCH models for volatility forecasting, the strategy's positions and exposures are dynamically adjusted. The results indicate that such an approach can enhance returns in volatile markets, suggesting potential for refined trading strategies in China's evolving derivatives landscape. The research underscores the importance of adaptive strategies in capturing market opportunities amidst changing trading dynamics.
Phase retrieval beyond the homogeneous object assumption for X-ray in-line holographic imaging

X-ray near field holography has proven to be a powerful 2D and 3D imaging technique with applications ranging from biomedical research to material sciences. To reconstruct meaningful and quantitative images from the measurement intensities, however, it relies on computational phase retrieval which in many cases assumes the phase-shift and attenuation coefficient of the sample to be proportional. Here, we demonstrate an efficient phase retrieval algorithm that does not rely on this homogeneous-object assumption and is a generalization of the well-established contrast-transfer-function (CTF) approach. We then investigate its stability and present an experimental study comparing the proposed algorithm with established methods. The algorithm shows superior reconstruction quality compared to the established CTF-based method at similar computational cost. Our analysis provides a deeper fundamental understanding of the homogeneous object assumption and the proposed algorithm will help improve the image quality for near-field holography in biomedical applications
Are your comments outdated? Towards automatically detecting code-comment consistency

In software development and maintenance, code comments can help developers understand source code, and improve communication among developers. However, developers sometimes neglect to update the corresponding comment when changing the code, resulting in outdated comments (i.e., inconsistent codes and comments). Outdated comments are dangerous and harmful and may mislead subsequent developers. More seriously, the outdated comments may lead to a fatal flaw sometime in the future. To automatically identify the outdated comments in source code, we proposed a learning-based method, called CoCC, to detect the consistency between code and comment. To efficiently identify outdated comments, we extract multiple features from both codes and comments before and after they change. Besides, we also consider the relation between code and comment in our model. Experiment results show that CoCC can effectively detect outdated comments with precision over 90%. In addition, we have identified the 15 most important factors that cause outdated comments, and verified the applicability of CoCC in different programming languages. We also used CoCC to find outdated comments in the latest commits of open source projects, which further proves the effectiveness of the proposed method.
Learning interacting fermionic Hamiltonians at the Heisenberg limit

Efficiently learning an unknown Hamiltonian given access to its dynamics is a problem of interest for quantum metrology, many-body physics and machine learning. A fundamental question is whether learning can be performed at the Heisenberg limit, where the Hamiltonian evolution time scales inversely with the error, $\varepsilon$, in the reconstructed parameters. The Heisenberg limit has previously been shown to be achievable for certain classes of qubit and bosonic Hamiltonians. Most recently, a Heisenberg-limited learning algorithm was proposed for a simplified class of fermionic Hubbard Hamiltonians restricted to real hopping amplitudes and zero chemical potential at all sites, along with on-site interactions. In this work, we provide an algorithm to learn a more general class of fermionic Hubbard Hamiltonians at the Heisenberg limit, allowing complex hopping amplitudes and nonzero chemical potentials in addition to the on-site interactions, thereby including several models of physical interest. The required evolution time across all experiments in our protocol is $\mathcal{O}(1/\varepsilon)$ and the number of experiments required to learn all the Hamiltonian parameters is $\mathcal{O}(\text{polylog}(1/\varepsilon))$, independent of system size as long as each fermionic mode interacts with $\mathcal{O}(1)$ other modes. Unlike prior algorithms for bosonic and fermionic Hamiltonians, to obey fermionic parity superselection constraints in our more general setting, our protocol utilizes $\mathcal{O}(N)$ ancillary fermionic modes, where $N$ is the system size. Each experiment involves preparing fermionic Gaussian states, interleaving time evolution with fermionic linear optics unitaries, and performing local occupation number measurements on the fermionic modes. The protocol is robust to a constant amount of state preparation and measurement error.
Scaling up Dynamic Edge Partition Models via Stochastic Gradient MCMC

The edge partition model (EPM) is a generative model for extracting an overlapping community structure from static graph-structured data. In the EPM, the gamma process (GaP) prior is adopted to infer the appropriate number of latent communities, and each vertex is endowed with a gamma distributed positive memberships vector. Despite having many attractive properties, inference in the EPM is typically performed using Markov chain Monte Carlo (MCMC) methods that prevent it from being applied to massive network data. In this paper, we generalize the EPM to account for dynamic enviroment by representing each vertex with a positive memberships vector constructed using Dirichlet prior specification, and capturing the time-evolving behaviour of vertices via a Dirichlet Markov chain construction. A simple-to-implement Gibbs sampler is proposed to perform posterior computation using Negative- Binomial augmentation technique. For large network data, we propose a stochastic gradient Markov chain Monte Carlo (SG-MCMC) algorithm for scalable inference in the proposed model. The experimental results show that the novel methods achieve competitive performance in terms of link prediction, while being much faster.
Development of a New Generation of Inoculants for Ti-Al Alloys

Les alliages Ti-Al sont depuis peu utilises industriellement dans le domaine aeronautique. Il est necessaire d’affiner les grains dans ces alliages en evitant la formation des precipites. Une nouvelle methode d’inoculation appelee inoculation isomorphe a ete developpee ou les particules agissent comme des sites de croissance plutot que comme des sites de germination, evitant ainsi la barriere d’energie pour la germination. Trois alliages inoculants ont ete developpes, les deux premiers, Ti-10Al-25Nb et Ti-25Al-10Ta, allient une bonne coherence du parametre de maille avec l’alliage de base et une bonne stabilite dans le liquide. Le troisieme, Ti-47Ta, met en avant l’aspect stabilite. Les coulees ont montre que les premiers deux alliages ont affine les grains sans laisser de particules heterogenes. L’alliage binaire Ti-Ta a une densite trop importante et les particules ont sedimentees dans le lingot ou elles n’ont pas pu jouer leur role. L’efficacite des inoculants est superieure a l’unite, chaque particule etant responsable de la formation de plus d’un nouveau grain. Ce dernier effet est attribue a la polycristallinite des inoculants qui peuvent se fragmenter par dissolution preferentielle aux joints de grains. Les calculs prenant en compte la fragmentation et la dissolution indiquent des efficacites proches de l’unite, ce qui confirme les valeurs experimentales d’efficacite anormalement elevees
Gender Bias in Large Language Models across Multiple Languages

With the growing deployment of large language models (LLMs) across various applications, assessing the influence of gender biases embedded in LLMs becomes crucial. The topic of gender bias within the realm of natural language processing (NLP) has gained considerable focus, particularly in the context of English. Nonetheless, the investigation of gender bias in languages other than English is still relatively under-explored and insufficiently analyzed. In this work, We examine gender bias in LLMs-generated outputs for different languages. We use three measurements: 1) gender bias in selecting descriptive words given the gender-related context. 2) gender bias in selecting gender-related pronouns (she/he) given the descriptive words. 3) gender bias in the topics of LLM-generated dialogues. We investigate the outputs of the GPT series of LLMs in various languages using our three measurement methods. Our findings revealed significant gender biases across all the languages we examined.
Journal of Geophysical Research : Solid Earth A Preseismic Strain Anomaly Detected Before M 6 Earthquakes in the South Iceland Seismic Zone From GPS Station Velocities

The South Iceland Seismic Zone (SISZ) accommodates E-W translation due to oblique spreading between the North American and the Eurasian plates in South Iceland with ruptures on N-S faults. Strain is released in earthquake sequences that last days to years, at average intervals of 80–100 years. Two M6.5 earthquakes struck in the SISZ in June 2000, and two M6 earthquakes in May 2008. These events released only half of the strain accumulated since the last earthquake sequence in 1896–1912. GPS station velocities are estimated from annual campaigns and continuous measurements in the SISZ during 2001–2015. The GPS station velocities are used to calculate strain rates from a new method using the vertical derivatives of horizontal stress. Our new strain rates are obtained by integrating vertical derivatives of horizontal stress rates, rather than differentiating interpolated GPS velocities, allowing finer resolution of strain. Estimating the strain rates for eight time intervals, we find high strain rates in the SISZ (0.5–1 microstrain per year) with significant temporal and spatial variation. The strain rates in the SISZ reveal contraction in the Hengill area and dilatation over a large area in eastern SISZ, indicating inflation of the magma system beneath Hekla volcano. A prominent strain anomaly is evident in the epicentral area prior to the May 2008 earthquakes. We suggest that this signal is primarily caused by plate motion and an increase in the rate of contraction in the Hengill area, located ∼10 km west of the epicentral area.