Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolution Trend Analysis of Agro-Ecosystem in Shijiazhuang City Area

By using emergy analysis method,a trend analysis was made on the total energy,input-output structure,and energy indices of agro-ecosystem in Shijiazhuang area for 2005 to 2010.The result showed that in the studied period,the total energy input of agro-ecosystem in Shijiazhuang city was in a decreasing tendency,total energy output was basically maintained at a stable level,and the efficiency of energy output increased by 8.1%. The input structure was almost stable,agricultural production was mainly based on input of industry supplemental energy.The proportion of animal husbandry and farming in total energy output showed certain shift.Farming energy consumption has transferred to the grain and fruit,the consumption of animal husbandry product transferred from pig,beef and mutton to poultry,milk and honey.Shijiazhuang agro-ecological economic system had better function as a whole with low dependence on natural resources and higher security for food production,but total auxiliary energy input had little room to increase.Shijiazhuang agroecosystem had powerful sustainable development capacity and greater space to develop,but simultaneously it led some pressure to the ecological environment.Shijiazhuang city should adjust the structure of agricutural input and output energy,strengthen the research of agricultural science,and develop eco-agriculture to promote sustainability of its agricultural development.
An investment case analysis for the prevention and treatment of adolescent mental disorders and suicide in England

Abstract Background Adolescent mental health (AMH) needs in England have increased dramatically and needs exceed treatment availability. This study undertook a comparative assessment of the health and economic return on investment (ROI) of interventions to prevent and treat mental disorders among adolescents (10–19 years) and examined intervention affordability and readiness. Methods Interventions were identified following a review of published and grey literature. A Markov model followed a simulated adolescent cohort to estimate implementation costs and health, education, and economic benefits. Intervention affordability was assessed, comparing annual cost per adolescent with NHS England per capita spending, and an expert panel assessed intervention readiness using a validated framework. Results Over 10- and 80-year horizons, interventions to treat mild anxiety and mild depression were most cost-effective, with the highest individual lifetime ROI (GBP 5822 GBP 1 and GBP 257: GBP 1). Preventing anxiety and depression was most affordable and ‘implementation ready’ and offered the highest health and economic benefits. A priority package (anxiety and depression prevention; mild anxiety and mild depression treatment) would avert 5 million disability-adjusted life-years (DALYS) and achieve an ROI of GBP 15: GBP 1 over 10 years or 11.5 million DALYs (ROI of GBP 55: GBP 1) over 80 years. Conclusion The economic benefits from preventing and treating common adolescent mental disorders equivalent to 25% of NHS England’s annual spending in 2021 over 10 years and 91% over 80 years. Preventing and early treatment for anxiety and depression had the highest ROIs and strong implementation readiness.
Adversarial Medical Image with Hierarchical Feature Hiding

Deep learning based methods for medical images can be easily compromised by adversarial examples (AEs), posing a great security flaw in clinical decision-making. It has been discovered that conventional adversarial attacks like PGD which optimize the classification logits, are easy to distinguish in the feature space, resulting in accurate reactive defenses. To better understand this phenomenon and reassess the reliability of the reactive defenses for medical AEs, we thoroughly investigate the characteristic of conventional medical AEs. Specifically, we first theoretically prove that conventional adversarial attacks change the outputs by continuously optimizing vulnerable features in a fixed direction, thereby leading to outlier representations in the feature space. Then, a stress test is conducted to reveal the vulnerability of medical images, by comparing with natural images. Interestingly, this vulnerability is a double-edged sword, which can be exploited to hide AEs. We then propose a simple-yet-effective hierarchical feature constraint (HFC), a novel add-on to conventional white-box attacks, which assists to hide the adversarial feature in the target feature distribution. The proposed method is evaluated on three medical datasets, both 2D and 3D, with different modalities. The experimental results demonstrate the superiority of HFC, i.e., it bypasses an array of state-of-the-art adversarial medical AE detectors more efficiently than competing adaptive attacks1, which reveals the deficiencies of medical reactive defense and allows to develop more robust defenses in future.
Lowered social motivation is associated with adolescent attention deficit hyperactivity disorder and social anxiety symptoms

Background Difficulties in social skills are highly prevalent in children and adolescents with attention deficit hyperactivity disorder (ADHD), however, the reasons for these social difficulties are poorly understood. This study aimed to understand social motivation in children (aged 5–8) and adolescents (aged 13–17) with and without ADHD, and the relationship between social anxiety and social motivation in youth with ADHD. Method 204 parents of children and adolescents with and without ADHD completed online questionnaires on social motivation, social anxiety, and ADHD symptoms. Results Adolescents with ADHD had significantly lower social motivation than typically developing adolescents, and children with ADHD. Higher social anxiety significantly predicted lowered social motivation in participants with ADHD. Conclusions These findings indicate a unique pattern of social motivation in ADHD, specifically a reduction during adolescence, reflecting social intervention inefficacy. Additionally, these findings establish a link between social motivation and social anxiety, suggesting that they may act as barriers to social intervention.
Systemic lupus erythematosus is associated with lower risk of hepatitis B virus infection: A multivariable Mendelian randomization study in East Asian population

The relationship between systemic lupus erythematosus (SLE) and hepatitis B virus (HBV) infection is still unclear. We conducted a two‐sample Mendelian randomization (MR) analysis using summary statistics from genome‐wide association studies for SLE and HBV infection in individuals of East Asian ancestry. The inverse‐variance weighted (IVW) method, weighted median (WM) method, and MR‐Egger method were used to estimate the causal effect of SLE on HBV infection. Additionally, we performed a multivariable MR analysis adjusting for the effects of body mass index and rheumatoid arthritis. This MR study included a total of 225 106 individuals of East Asian ancestry, comprising 5616 cases and 219 490 controls. The IVW method (OR: 0.79, p = 3.34E−08) and the WM method (OR: 0.79, p = 9.09E−06) revealed a causal relationship between genetically predicted SLE and a low risk of HBV infection. The multivariable MR analysis still suggested a low risk of HBV infection associated with SLE (OR: 0.83, p = 2.89E−06). Our MR analysis supports a causal relationship between SLE and a low risk of HBV infection in individuals of East Asian ancestry.
Enhancing EEG-based cross-day mental workload classification using periodic component of power spectrum

Objective. The day-to-day variability of electroencephalogram (EEG) poses a significant challenge to decode human brain activity in EEG-based passive brain-computer interfaces (pBCIs). Conventionally, a time-consuming calibration process is required to collect data from users on a new day to ensure the performance of the machine learning-based decoding model, which hinders the application of pBCIs to monitor mental workload (MWL) states in real-world settings. Approach. This study investigated the day-to-day stability of the raw power spectral density (PSD) and their periodic and aperiodic components decomposed by the Fitting Oscillations and One-Over-F algorithm. In addition, we validated the feasibility of using periodic components to improve cross-day MWL classification performance. Main results. Compared to the raw PSD (69.9% ± 18.5%) and the aperiodic component (69.4% ± 19.2%), the periodic component had better day-to-day stability and significantly higher cross-day classification accuracy (84.2% ± 11.0%). Significance. These findings indicate that periodic components of EEG have the potential to be applied in decoding brain states for more robust pBCIs.
Correlations Between Reflectance Spectra and Contents of Chlorophyll-a in Chaohu Lake

Chaohu Lake is one of the biggest freshwater lakes of China. This study was conducted to establish correlations between reflectance spectra and contents of chlorophyll a in Chaohu Lake, which was in eutrophic status. Reflectance spectra were measured during November, 2001 by using ASD FieldSpec HandHeld radiometer. Water samples for chlorophyll a measurements and dominant algal species determination were collected at the same time. The features of the spectral reflectance of the lake were discussed. The correlation between the spectral reflectance of single band and the content of chlorophyll a was low. The reflectance ratio of R 705nm / R 680nm and the reflectance first derivative of 690nm were found to be significantly correlated with the contents of chlorophyll a, and the r 2 gained using the reflectance ratio was higher than gained from the reflectance first derivative of 690nm's.
Responding restoratively to elder harm: lessons from a pilot scheme in Aotearoa New Zealand

ABSTRACT The search for adequate ways to address elder harm and abuse has become increasingly evident in public discourse. There is a growing consensus that integrated, multi-disciplinary approaches are needed, especially because older victims are often hesitant to resort to legal interventions. This evaluation study aimed to assess the benefits and challenges of a pilot scheme in Aotearoa New Zealand employing restorative processes to respond to elder harm and to discuss implications for future practice. Thirty interviews were conducted with professionals, older persons and family members. Our findings show that restorative encounters, in particular circle processes, provided a safe environment to engage honestly with each other and for mutual understanding and trust to emerge. The collaborative relationship of key stakeholders was a notable strength of the pilot. However, the major challenge in using restorative practices was dealing adequately with long and complex histories of family conflicts.
Effects of adding glucosamine or glucosamine combined with chondroitin to exercise on pain and physical function in adults with knee osteoarthritis: a systematic review and meta-analysis

It is well known that different types of exercise significantly improve physical function and relieve pain in knee osteoarthritis (KOA) patients. The aim of this study was to investigate the added effects of glucosamine or glucosamine and chondroitin supplementation in combination with an exercise program in the management of KOA. The randomized controlled trials on adding glucosamine (G) or G combined with chondroitin (C) to an exercise program in the treatment of KOA were searched in the PubMed, Cochrane Central Register of Controlled Trials, PEDro, and Web of Science online databases. The Pedro scale tool was used to assess quality of literature. A meta-analysis was performed using the Review Manager 5.4 software. In total, 6 studies (including 297 participants) were included for the final meta-analysis. According to the PEDro scale, the average quality of the studies was rated as good (mean = 8.2(2)). The results showed that the effect of G, or G and C, in combination with exercise is not significant, as indicated by the assessed knee pain (WOMAC pain: SMD -0.18, 95% CI -0.47 to 0.11, p = 0.23; and VAS pain: SMD -0.34, 95% CI -0.85 to 0.17, p = 0.20) and physical function (SMD -0.13, 95% CI -0.95 to 0.69, p = 0.76). Adding glucosamine alone or a combination of glucosamine and chondroitin to exercise, has no effect on knee pain and physical function compared with exercise alone in KOA patients.
Do community-based singing interventions have an impact on people living with dementia and their carers? A mixed-methods study protocol

Introduction Psychosocial interventions have been shown to improve mood, relieve stress and improve quality of life for people living with dementia (PwD). To date, most evaluations of singing interventions have focused on the benefits for PwD and not their carers. This research aims to evaluate the benefits of dementia singing groups for both PwD and their carers. Methods and analysis This 2-year project will observe the impact of two different singing intervention services, one combining singing alongside dance and another that includes a sociable lunch. This project will aim to recruit a total of n=150 PwD and n=150 carers across the two singing interventions. Using a mixed-methods approach, the influence of both services will be analysed via the following outcome measures: quality of life, neuropsychiatric symptoms, social isolation, loneliness, cognition, carer burden and depressive symptoms in PwD and their carers using a prestudy/poststudy design. Regression models will be used to analyse the data with time (pre/post) as the exposure variable. Semistructured interviews will be conducted with a subset of people (n=40) to further investigate the impact of singing services with a specific focus on the acceptability of the interventions, barriers to access and prolonged engagement and potential for remote delivery. Interview data will be analysed using Braun and Clarke’s reflexive thematic analysis, and public advisers will assist with coding the transcripts. A social return on investment analysis will be conducted to determine the social impact of the services. Ethics and dissemination This project has received ethical approval from the University of Liverpool’s Ethics Committee (App ref: 12374) and Lancaster University’s Ethics Committee (App ref: 3442). All participants will provide informed consent to participate. Results will be presented at national and international conferences, published in scientific journals and publicly disseminated to key stakeholders.
Outcomes of dual‐chamber implantable cardioverter defibrillator for left bundle branch area pacing: A systematic review of literature

Abstract Objective This systematic review of literature aimed to evaluate the safety and efficacy of dual‐chamber ICDs for LBBAP in patients with left bundle branch block (LBBB). Methods Digital databases were searched systematically to identify studies reporting the left bundle branch area pacing (LBBAP) with implantable cardioverter defibrillator (ICD) placement in patients with LBBB. Detailed study and patient‐level baseline characteristics including the type of study, sample size, follow‐up, number of cases, age, gender, and baseline characteristics were abstracted. Results In a total of three studies, 34 patients were included in this review. There was a significant improvement reported in QRS duration in all studies. The mean QRS duration at baseline was 170 ± 17.4 ms, whereas the follow‐up QRS duration at follow‐up was 121 ± 17.3 ms. Two studies reported a significant improvement of 50% in LVEF from baseline. No lead‐related complications or arrhythmic events were recorded in any study. The findings of the systematic review suggest that dual‐chamber ICD for LBBAP is a promising intervention for patients with heart conditions. Conclusion The procedure offers significant improvements in QRS duration and LVEF, and there were no lead‐related complications or arrhythmic events recorded in any of the studies.
Matrix-Variate Regression for Sparse, Low-Rank Estimation of Brain Connectivities Associated With a Clinical Outcome

<italic>Objective:</italic> We address the problem of finding brain connectivities that are associated with a clinical outcome or phenotype. <italic>Methods:</italic> The proposed framework regresses a (scalar) clinical outcome on matrix-variate predictors which arise in the form of brain connectivity matrices. For example, in a large cohort of subjects we estimate those regions of functional connectivities that are associated with neurocognitive scores. We approach this high-dimensional yet highly structured estimation problem by formulating a regularized estimation process that results in a low-rank coefficient matrix having a sparse set of nonzero entries which represent regions of biologically relevant connectivities. In contrast to the recent literature on estimating a sparse, low-rank matrix from a single noisy observation, our scalar-on-matrix regression framework produces a data-driven extraction of structures that are associated with a clinical response. The method, called <bold>Sp</bold>arsity <bold>I</bold>nducing <bold>N</bold>uclear-<bold>N</bold>orm <bold>E</bold>stimato<bold>r</bold> (SpINNEr), simultaneously constrains the regression coefficient matrix in two ways: a nuclear norm penalty encourages low-rank structure while an <inline-formula><tex-math notation="LaTeX">$\ell _{1}$</tex-math></inline-formula> norm encourages entry-wise sparsity. <italic>Results:</italic> Our simulations show that SpINNEr outperforms other methods in estimation accuracy when the response-related entries (representing the brain's functional connectivity) are arranged in well-connected communities. SpINNEr is applied to investigate associations between HIV-related outcomes and functional connectivity in the human brain. <italic>Conclusion and Significance:</italic> Overall, this work demonstrates the potential of SpINNEr to recover sparse and low-rank estimates under scalar-on-matrix regression framework.
Flower visitor groups show differential responses to individual and plot-level chemodiversity with consequences for plant fitness

Chemodiversity, the diversity of specialised metabolites, plays a crucial role in mediating interactions between plants and animals, including insect herbivores and mutualists. Chemodiversity can be observed at both the individual and the population level. However, the impacts of chemodiversity at these two levels on interactions between plants and floral visitors, mainly pollinators and floral herbivores (florivores), are only poorly understood. This study aimed to investigate the effects of chemodiversity at both individual and plot level on pollinators and florivores, examining their mutual interactions. To investigate these questions, we used individuals of the perennial Tanacetum vulgare differing in their terpenoid composition, representing so-called chemotypes. We planted individuals of five distinct chemotypes in a common garden design with homogeneous (five plants of the same chemotype) and heterogeneous (five different chemotypes) plots and observed flower visits in dependence of individual chemotype and plot type. Seeds were collected from a subset of plants and germination rates determined. Our findings revealed that chemodiversity at the plot level significantly influenced pollinator visitation, with more visits on plants of heterogeneous plots. We also observed marginally more pollinators on one of the chemotypes grown in homogeneous plots. In contrast, chemotype but not plot type had a significant effect on florivore visits. Pollinator and florivore species richness did not vary with plot type. Furthermore, a negative correlation was observed between pollinator and florivore visits in one year, suggesting competitive interactions between these two groups. Germination rates were positively correlated with pollinator visits and affected by chemotype but not by florivore visits or plot type. Synthesis. Our study emphasizes the significance of the scale at which different chemical profiles are perceived by flower visitors, potentially influencing the reproductive fitness of plants. Exploring the ecology of these visitors and the varying selection pressures they exert on floral chemistry can help elucidating the evolutionary processes that maintain chemodiversity in natural environments.
Polyglucosan body density in the aged mouse hippocampus is controlled by a novel modifier locus on chromosome 1

Aging can be associated with the accumulation of hypobranched glycogen molecules (polyglucosan bodies, PGBs), particularly in astrocytes of the hippocampus. While PGBs have a detrimental effect on cognition in diseases such as adult polyglucosan body disease and Lafora disease, the underlying mechanism and clinical relevance of age-related PGB accumulation remains unknown. Here, we have investigated the genetic basis and functional impact of age-related PGB accumulation in 32 fully sequenced BXD-type strains of mice which exhibit a 400-fold variation in PGB burden in 16-18 month old females. We mapped a major locus controlling PGB density in the hippocampus to chromosome 1 at 72–75 Mb (linkage of 4.9 –logP), which we defined as the Pgb1 locus. To identify potentially causal gene variants within Pgb1, we generated extensive hippocampal transcriptome datasets and identified two strong candidate genes for which mRNA correlates with PGB density—Smarcal1 and Usp37. In addition, both Smarcal1 and Usp37 contain non-synonymous allele variations likely to impact protein function. A phenome-wide association analysis highlighted a trans-regulatory effect of the Pgb1 locus on expression of Hp1bp3, a gene known to play a role in age-related changes in learning and memory. To investigate the potential impact of PGBs on cognition, we performed conditioned fear memory testing on strains displaying varying degrees of PGB burden, and a phenome-wide association scan of ~12,000 traits. Importantly, we did not find any evidence suggesting a negative impact of PGB burden on cognitive capacity. Taken together, we have identified a major modifier locus controlling PGB burden in the hippocampus and shed light on the genetic architecture and clinical relevance of this strikingly heterogeneous hippocampal phenotype.
Dynamics of dominance: maneuvers, contests, and assessment in the posture-scale movements of interacting zebrafish

While two-body fighting behavior occurs throughout the animal kingdom to settle dominance disputes, important questions such as how the dynamics ultimately lead to a winner and loser are unresolved. Here we examine fighting behavior at high-resolution in male zebrafish. We combine multiple cameras, a large volume containing a transparent interior cage to avoid reflection artifacts, with computer vision to track multiple body points across multiple organisms while maintaining individual identity in 3D. In the body point trajectories we find a spectrum of timescales which we use to build informative joint coordinates consisting of relative orientation and distance. We use the distribution of these coordinates to automatically identify fight epochs, and we demonstrate the post-fight emergence of an abrupt asymmetry in relative orientations-a clear and quantitative signal of hierarchy formation. We identify short-time, multi-animal behaviors as clustered transitions between joint configurations, and show that fight epochs are spanned by a subset of these clusters, which we denote as maneuvers. The resulting space of maneuvers is rich but interpretable, including motifs such as “attacks” and “circling”. In the longer-time dynamics of maneuver frequencies we find differential and changing strategies, including that the eventual loser attacks more often towards the end of the contest. Our results suggest a reevaluation of relevant assessment models in zebrafish, while our approach is generally applicable to other animal systems.