Miracle-dz/UniFAR-FTUs huggingface dataset:
Functional magnetic resonance imaging progressive deformable registration based on a cascaded convolutional neural network.

Background Intersubject registration of functional magnetic resonance imaging (fMRI) is necessary for group analysis. Accurate image registration can significantly improve the results of statistical analysis. Traditional methods are achieved by using high-resolution structural images or manually extracting functional information. However, structural alignment does not necessarily lead to functional alignment, and manually extracting functional features is complicated and time-consuming. Recent studies have shown that deep learning-based methods can be used for deformable image registration. Methods We proposed a deep learning framework with a three-cascaded multi-resolution network (MR-Net) to achieve deformable image registration. MR-Net separately extracts the features of moving and fixed images via a two-stream path, predicts a sub-deformation field, and is cascaded three times. The moving and fixed images' deformation field is composed of all sub-deformation fields predicted by the MR-Net. We imposed large smoothness constraints on all sub-deformation fields to ensure their smoothness. Our proposed architecture can complete the progressive registration process to ensure the topology of the deformation field. Results We implemented our method on the 1000 Functional Connectomes Project (FCP) and Eyes Open Eyes Closed fMRI datasets. Our method increased the peak t values in six brain functional networks to 19.8, 17.8, 15.0, 16.4, 17.0, and 13.2. Compared with traditional methods [i.e., FMRIB Software Library (FSL) and Statistical Parametric Mapping (SPM)] and deep learning networks [i.e., VoxelMorph (VM) and Volume Tweening Network (VTN)], our method improved 47.58%, 11.88%, 18.60%, and 15.16%, respectively. Conclusions Our three-cascaded MR-Net can achieve statistically significant improvement in functional consistency across subjects.
An automated approach to identify scientific publications reporting pharmacokinetic parameters

Pharmacokinetic (PK) predictions of new chemical entities are aided by prior knowledge from other compounds. The development of robust algorithms that improve preclinical and clinical phases of drug development remains constrained by the need to search, curate and standardise PK information across the constantly-growing scientific literature. The lack of centralised, up-to-date and comprehensive repositories of PK data represents a significant limitation in the drug development pipeline.In this work, we propose a machine learning approach to automatically identify and characterise scientific publications reporting PK parameters from in vivo data, providing a centralised repository of PK literature. A dataset of 4,792 PubMed publications was labelled by field experts depending on whether in vivo PK parameters were estimated in the study. Different classification pipelines were compared using a bootstrap approach and the best-performing architecture was used to develop a comprehensive and automatically-updated repository of PK publications. The best-performing architecture encoded documents using unigram features and mean pooling of BioBERT embeddings obtaining an F1 score of 83.8% on the test set. The pipeline retrieved over 121K PubMed publications in which in vivo PK parameters were estimated and it was scheduled to perform weekly updates on newly published articles. All the relevant documents were released through a publicly available web interface (https://app.pkpdai.com) and characterised by the drugs, species and conditions mentioned in the abstract, to facilitate the subsequent search of relevant PK data. This automated, open-access repository can be used to accelerate the search and comparison of PK results, curate ADME datasets, and facilitate subsequent text mining tasks in the PK domain.
Intervening Role of Performance-Based Budgeting in the Relationship between Transformational Leadership, Organizational Commitment and University Performance

This study aims to investigate the influence of transformational leadership and organizational commitment on performance-based budgeting systems of Indonesian universities. It also examines the impact of performance-based budgeting systems on universities' performance and the role of performance-based budgeting as an intervening variable. The population in this study was private universities registered in Indonesian Higher Education Service Institutions (or Lembaga Layanan Pendidikan Tinggi / LLDikti) region XIII Aceh, Indonesia. The samples were selected using convenience sampling method. There were 130 completed questionnaires collected and analyzed using Partial Least Square. This study found that transformational leadership and organizational commitment have no direct effect on university performance, while the performance-based budgeting system has a significant positive effect on the performance of universities. This study also found that a performance-based budgeting system serves as an intervening variable in the relationship between transformational leadership and organizational commitment concerning higher education performance.
Optimal Surplus-Dependent Reinsurance under Regime-Switching in a Brownian Risk Model

In this paper, we consider a company that wishes to determine the optimal reinsurance strategy minimising the total expected discounted amount of capital injections needed to prevent the ruin. The company’s surplus process is assumed to follow a Brownian motion with drift, and the reinsurance price is modelled by a continuous-time Markov chain with two states. The presence of regime-switching substantially complicates the optimal reinsurance problem, as the surplus-independent strategies turn out to be suboptimal. We develop a recursive approach that allows to represent a solution to the corresponding Hamilton–Jacobi–Bellman (HJB) equation and the corresponding reinsurance strategy as the unique limits of the sequence of solutions to ordinary differential equations and their first- and second-order derivatives. Via Ito’s formula, we prove the constructed function to be the value function. Two examples illustrate the recursive procedure along with a numerical approach yielding the direct solution to the HJB equation.
Quantification of β-Sitosterol using HPTLC from Capparis decidua (Forsk.) Edgew.

Capparis decidua (Gudhapatra) is traditionally used for curing a variety of ailments such as toothache, cough, asthma, intermittent fever and rheumatism in India. There are no reports of quantification of β- Sitosterol from this plant. Hence a TLC densitometric method has been developed and validated for quantification of this marker compound. β-Sitosterol was quantified from methanolic extract using the Solvent System of Toluene: Methanol (9: 1, v/v). The method was validated using ICH guidelines in terms of precision, repeatability and accuracy. Linearity range for β-Sitosterol was 80–480 ng/spot and its content was 0.0244 % w/w. This simple, precise and accurate method gave good resolution from other constituents of extract. It can be adopted for routine quality control of herbal material and formulations containing Capparis decidua.
Card collection: An examination of whether yellow and red cards affect base salary under Major League Soccer’s salary cap

We examine the effect of card (yellow and red) collection on player remuneration under the salary cap in Major League Soccer (MLS). The data contain 1478 observations of 731 players under contract between 2015 and 2019. Though the number of yellow cards a player collected had a significant impact, the number of red cards collected was not found to be a significant factor. On average, when a player has accumulated more than eight yellow cards over the course of the regular season, his salary was dropped substantially. If a player receives more than two red cards, his salary was decreased. A key result was that players who were aggressive without crossing the line to the point of being ejected from the field of play received comparatively higher salaries.
Hybrid LoRa-IEEE 802.11s Opportunistic Mesh Networking for Flexible UAV Swarming

Unmanned Aerial Vehicles (UAVs) and small drones are nowadays being widely used in heterogeneous use cases: aerial photography, precise agriculture, inspections, environmental data collection, search-and-rescue operations, surveillance applications, and more. When designing UAV swarm-based applications, a key “ingredient” to make them effective is the communication system (possible involving multiple protocols) shared by flying drones and terrestrial base stations. When compared to ground communication systems for swarms of terrestrial vehicles, one of the main advantages of UAV-based communications is the presence of direct Line-of-Sight (LOS) links between flying UAVs operating at an altitude of tens of meters, often ensuring direct visibility among themselves and even with some ground Base Transceiver Stations (BTSs). Therefore, the adoption of proper networking strategies for UAV swarms allows users to exchange data at distances (significantly) longer than in ground applications. In this paper, we propose a hybrid communication architecture for UAV swarms, leveraging heterogeneous radio mesh networking based on long-range communication protocols—such as LoRa and LoRaWAN—and IEEE 802.11s protocols. We then discuss its strengths, constraints, viable implementation, and relevant reference use cases.
Effects of wage-peak system on youth employment: Evidence from South Korea

ABSTRACT After the increase in the minimum retirement age, South Korea introduced a wage-peak system to mitigate increases in firm costs due to the wage of elderly workers. In this study, we examined how the later retirement age has affected employment opportunities for younger workers. We also investigated the difference in impact of later retirement on employment between firms within and outside of the system. Using the difference-in-differences empirical method, we found that this system has increased employment opportunities for younger workers. Moreover, as the proportion of elderly workers increases, the effect of the wage-peak system on the proportion of young workers is enhanced.
Improving the Constraint on the Mw 7.1 2016 Off‐Fukushima Shallow Normal‐Faulting Earthquake With the High Azimuthal Coverage Tsunami Data From the S‐Net Wide and Dense Network: Implication for the Stress Regime in the Tohoku Overriding Plate

Tsunamis with amplitudes of up to 40 cm, related to the Mw 7.1 normal‐faulting earthquake off Fukushima, Japan, on November 21, 2016, were clearly recorded by a new offshore wide and dense ocean‐bottom pressure gauge network, S‐net, with high azimuthal coverage located closer to the focal area. We processed the S‐net data and found some stations included the tsunami‐irrelevant drift and step signals. We analyzed the S‐net data to infer the tsunami source distribution. A subsidence region with a narrow spatial extent (∼40 km) and a large peak (∼200 cm) was obtained. The other near‐coastal waveforms not used for the inversion analysis were also reproduced very well. Our fault model suggests the maximum stress drop across the fault plane of >∼10 MPa and the average of 4.2 MPa, whereas the shear stress increase along the fault caused by the 2011 Tohoku earthquake was only ∼2 MPa. Past studies have suggested that horizontal compressional stress around this region switched to horizontal extensional stress after the Tohoku earthquake due to its stress perturbation. The present result, however, suggests that the horizontal extensional stress was locally predominant at the shallowest surface around the focal area even before 2011. The present study demonstrates that the S‐net high‐azimuthal‐coverage pressure data provide a significant constraint on the fault modeling, which enables us to discuss the stress regime within the overriding plate at the offshore. Our analysis provides an implication for crustal stress states, which is important for understanding generation mechanisms of intraplate earthquakes.
Developing flexibility for combat sports athletes

The range of motion of a joint is extremely important in combat sports, especially when there is a need to execute a certain motor gesture with maximum range of movement, as in throwing techniques such as uchi-mata in judo, certain types of guards in Brazilian jiu-jitsu or the high kicks common in a variety of striking combat sports. Therefore, in this chapter, we will discuss the elements related to flexibility response during training sessions or combat sports competitions, flexibility tests commonly used for these athletes, and the monitoring and control of the evolution of flexibility in athletes. We will also present the means and methods used for the development of flexibility and longitudinal studies on the development of flexibility in combat sports athletes. Finally, this chapter supports based on the evidence the inclusion of flexibility development within training sessions is an important consideration to maximize performance and other physical capabilities that may be affected both acutely or in the long-term by flexibility.
Influence of Polyethyleneimine and Ammonium on the Growth of ZnO Nanowires by Hydrothermal Method

In this study, ZnO nanowire arrays were prepared using a hydrothermal method. During growth, polyethyleneimine (PEI) and ammonia were added to adjust the structure and optical properties of the ZnO nanowires. Emission analysis revealed visible photoluminescence emissions from ZnO nanowires produced under various growth conditions. To correlate the relationship between visible emissions and structural defects in ZnO nanowires, we employed X-ray absorption spectroscopy (XAS) to characterize the coordination number and bond length of the ZnO nanowires. On the basis of analytical results, we determined that the red emission is attributed to interstitial zinc defects (Zni) and the yellow emission is attributed to interstitial oxygen defects (Oi).
Declining wintering shorebird populations at a temperate estuary in California: A 30-year perspective

ABSTRACT Worldwide, shorebird populations are declining. Our objectives were to examine abundance trends of shorebirds regularly wintering at Tomales Bay, Marin County, California, accounting for the local effects of rainfall, raptors, and the restoration of part of the bay to tidal wetlands. From November 1989 to February 2019, we conducted 177 comprehensive winter shorebird surveys of Tomales Bay; we averaged 5.7 ± 0.9 (mean ± SD) winter surveys per year. In 30 yr, we counted 1,215,821 shorebirds of 31 species. We used generalized linear models and multi-model inference to evaluate trends in shorebird abundance while accounting for local sources of variation. We conducted separate analyses for 14 species seen in at least 20 of the 30 yr of monitoring and for all shorebird species combined. During the study, the abundance of all species combined declined 66% (52% in the North Bay and 81% in the South Bay) with the most rapid decline in the first 10 yr of monitoring. Of 13 species for which year was in the top model, 10 species decreased in abundance and 3 species increased. Dunlin and Western Sandpiper accounted for the greatest losses in total numbers. The best-supported models to estimate trends in shorebirds included predictors for year and North Bay vs. South Bay. Of the local variables we considered, rainfall was included in 10 of the 15 best-supported models (including all species combined), negatively affecting the numbers of all species except Willets. The wetland restoration project was included in 5 top models, with a short-term positive impact. Raptor abundance was included in 3 top models with mixed results. Our results show that effective conservation and management of local shorebird populations must be linked with regional/global efforts if we are to reverse negative shorebird trends. LAY SUMMARY Given declining North American shorebird populations, we analyzed population trends of shorebirds wintering at Tomales Bay, Marin County, California, spanning 30 seasons from November 1989 to February 2019, and reasons for these trends. Survey teams counted over 1.2 million shorebirds of 31 species, of which we analyzed trends for 14 regularly occurring species. During this period, overall shorebird numbers declined by 66%; 10 species declined, 3 species increased, and 1 species did not change. Dunlin and Western Sandpiper suffered the greatest losses, while Least Sandpipers and yellowlegs (predominantly Greater Yellowlegs) increased the most. Effective conservation and management of local shorebird populations must be linked with regional/global efforts to reverse negative shorebird trends.
Locating the voices of Indigenous young people on identity in Australia: an Indigenist analysis

ABSTRACT The identities of Indigenous young people in Australia have increasingly been recognized in the health and education research literature as being significant. Over half of the Indigenous population in Australia is under the age of 25 years, emphasizing the importance of centering the voices of this cohort. In this paper, two Indigenous scholars undertake an Indigenist analysis of the ways that the voices of Indigenous young people are present within knowledge production about them in relation to their identities. This paper presents a number of themes that emerge from the analysis of how the voices of Indigenous young people in Australia are privileged in the literature, highlighting the significance of closer examination of knowledge paradigms and representations. Creating a deeper understanding of identity and the impact on wellbeing through their lens as Indigenous young people is critical for improving policy and program development as well as future research.
Clinical Practice of Hepatorenal Syndrome: A Brief Review on Diagnosis and Management

The hepatorenal syndrome is one of various potential causes of acute kidney injury in patients with decompensated liver disease. Hepatorenal syndrome is diagnosed based on reducing kidney function without any evidence of intrinsic kidney disease, including proteinuria, hematuria, or abnormal kidney ultrasonography. Clinically, hepatorenal syndrome is divided into two types named type 1 and type 2. The most favorable therapy for HRS cases is liver transplantation; however, only a few undergo this procedure due to the high mortality. Other modalities for hepatorenal syndrome therapy are pharmacology and non-pharmacology approaches. The purpose of management HRS is to optimize and stabilize the patient until an organ transplant available. This review aims to discuss the underlying pathophysiology and demonstrate the diagnostic approach of hepatorenal syndrome to determine the most appropriate therapeutic measures in clinical practice. The clinicians must be aware of management principles of hepatorenal syndrome to improve the quality of care for patients and optimize the clinical conditions.
Solving Fractional Differential Equations by Using Triangle Neural Network

In this paper, numerical methods for solving fractional differential equations by using a triangle neural network are proposed. The fractional derivative is considered Caputo type. The fractional derivative of the triangle neural network is analyzed first. Then, based on the technique of minimizing the loss function of the neural network, the proposed numerical methods reduce the fractional differential equation into a gradient descent problem or the quadratic optimization problem. By using the gradient descent process or the quadratic optimization process, the numerical solution to the FDEs can be obtained. The efficiency and accuracy of the presented methods are shown by some numerical examples. Numerical tests show that this approach is easy to implement and accurate when applied to many types of FDEs.
Has tourism driven house prices in Germany? Time-varying evidence since 1870

Using a historical data set and recent advances in non-parametric time series modelling, we investigate the nexus between tourism flows and house prices in Germany over nearly 150 years. We use time-varying non-parametric techniques given that historical data tend to exhibit abrupt changes and other forms of non-linearities. Our findings show evidence of a time-varying effect of tourism flows on house prices, although with mixed effects. The pre-World War II time-varying estimates of tourism show both positive and negative effects on house prices. While changes in tourism flows contribute to increasing housing prices over the post-1950 period, this is short-lived, and the effect declines until the mid-1990s. However, we find a positive and significant relationship after 2000, where the impact of tourism on house prices becomes more pronounced in recent years.
Development of an engineered probiotic for the treatment of branched chain amino acid related metabolic diseases

Metabolic dysfunction arising from missing or impaired enzymes comprising the branched chain amino acid (BCAA) degradation pathway, especially those involving leucine, can result in the accumulation of toxic metabolic intermediates and cause severe metabolic disease. Removal of dietary BCAAs via their degradation by engineered microbes could be a viable approach to prevent BCAA-mediated disease sequelae. In this article, we describe the design and construction of an engineered leucine degrading strain of E. coli Nissle, the improvement of the degradation pathway through high throughput screening, and the demonstration of strain activity in animal models monitored by disease and strain-specific biomarkers. This work provides a path for the development of engineered probiotic bacterial strains as a treatment for BCAA-related metabolic disorders in humans.
A computational approach to tracking age-based task frequency distributions of Apis mellifera worker cohorts

We present a model for tracking future task frequency distributions of individual adult worker honey bee (Apis mellifera L.) cohorts in a colony based on the composition of immatures at a specific time period. The user inputs the proportions of brood comb occupied by eggs, larvae, capped brood, or non-brood/empty cells. The model captured an experimental example where a brood comb is inserted into a surrogate colony and the individuals then emerge and express their adult lives. This model has clear application to many other experiments such as sublethal pesticide exposure. The model output is the expected proportion of cohort members engaged in a focal task at any given day post-insertion.
Fluorescent chiral liquid-crystalline networks with dual-mode temperature response

ABSTRACT Due to the excellent optical properties and great application prospects in the optical field, both pyrene compounds (PCs) and chiral liquid crystal have attracted extensive attention in theoretical research and practical applications. Fluorescent chiral liquid-crystalline networks (FCLCN) with good liquid-crystalline properties and tunable fluorescence properties as a response to temperature were prepared using Poly(methylhydrogeno)siloxane (PMHS), chiral liquid-crystalline monomer (M1), chiral crosslinker (M2) and organic fluorescent pyrene compounds (M3). The as-prepared FCLCN display reversible chiral Grandjean texture during the heating and cooling process from the intrinsic chiral arrangement of FCLCN. The discrete pyrene chromogenic segments in FCLCN matrix endowed the networks with excellent fluorescence properties when irradiating with ultraviolet light and the fluorescence can be precisely adjusted by temperature, furthermore, the FCLCN presents highly sensitive fluorescence evolution with a high response sensitivity of 3.4% K−1. The FCLCN can be manufactured into temperature-driven dynamic fluorescence patterns with a fast and reversible response. GRAPHICAL ABSTRACT