Miracle-dz/UniFAR-FTUs huggingface dataset:
Changes in biochemical markers following a spinal manipulation – a systematic review update

ABSTRACT Objective The aim of this systematic review was to update the current level of evidence for spinal manipulation in influencing various biochemical markers in healthy and/or symptomatic population. Methods This is a systematic review update. Various databases were searched (inception till May 2023) and fifteen trials (737 participants) that met the inclusion criteria were included in the review. Two authors independently screened, extracted and assessed the risk of bias in included studies. Outcome measure data were synthesized using standard mean differences and meta-analysis for the primary outcome (biochemical markers). The Grading of Recommendations, Assessment, Development and Evaluation (GRADE) was used for assessing the quality of the body of evidence for each outcome of interest. Results There was low-quality evidence that spinal manipulation influenced various biochemical markers (not pooled). There was low-quality evidence of significant difference that spinal manipulation is better (SMD −0.42, 95% CI − 0.74 to −0.1) than control in eliciting changes in cortisol levels immediately after intervention. Low-quality evidence further indicated (not pooled) that spinal manipulation can influence inflammatory markers such as interleukins levels post-intervention. There was also very low-quality evidence that spinal manipulation does not influence substance-P, neurotensin, oxytocin, orexin-A, testosterone and epinephrine/nor-epinephrine. Conclusion Spinal manipulation may influence inflammatory and cortisol post-intervention. However, the wider prediction intervals in most outcome measures point to the need for future research to clarify and establish the clinical relevance of these changes.
Association of rhinovirus and potentially pathogenic bacterial detections in the first 3 months of life with subsequent wheezing in childhood

Airway interactions between viruses, especially rhinoviruses, and potentially pathogenic bacteria (PPB; Streptococcus pneumoniae, Haemophilus influenzae, and Moraxella catarrhalis) in early infancy may increase the risk of subsequent wheezing and asthma. We evaluated the association between rhinovirus and PPB in the first 3 months of life and wheezing episodes before age 2 years and asthma at age 5–7 years.
Exploring options for agricultural development : a case study in China

Keywords: Linear programming; Land use model; Technology assessmen China's agriculture faces a series of challenges, i.e. guaranteeing national food security, increasing farmer's income and reducing the adverse effects on environment and human health associated with the use of fertilizers and biocides. At the same time, the availability of resources {e.g. agricultural land) decreases. The objective of this study is to operationalize a methodology to assess the effectiveness of new crop and livestock technologies in attaining rural development goals, using Jiangxi Province as a case study area. Cropping and livestock systems, quantified in terms of inputs and outputs, are used as the smallest unit of analysis in this study. The new, also referred to as alternative, cropping systems comprise cultivation of Super Rice varieties and introduction of site-specific nutrient management (SSNM), integrated pest management (IPM) and mechanization in rice production. In alternative livestock systems, improved animal breeds, chemical treatment of crop residues and improved management in animal husbandry are adopted. A regional land use model, based on linear programming techniques, is used to assess the contribution of these alternative cropping and livestock systems to rural development goals. The results indicate that adoption of Super Rice varieties is most effective in attaining national grain security, while integration of Super Rice with improved beef cattle fattening systems is most effective in increasing income. Competition between livestock and rice production is limited, since high quality feed can be produced in rotation with rice without requiring additional rice land, and on non-rice land. Both, SSNM and IPM are most effective in reducing adverse environmental and human health effects, but hardly improve economic returns. Mechanization of rice production strongly reduces labour requirements in agriculture, leads to higher returns to labour and provides opportunities to work off-farm. When both, alternative crop and livestock systems are adopted concurrently, the goals of grain security, increasing rural income and reducing environmental pollution can be realized simultaneously. Results of this study contribute to the formulation of agricultural policies and a research agenda aiming at stimulating rural development in China.
Coxsackievirus B3 elicits a sex-specific CD8+ T cell response which protects female mice

Sex is a significant contributor to the outcome of human infections. Males are frequently more susceptible to viral, bacterial, and fungal infections, often attributed to weaker immune responses. In contrast, a heightened immune response in females enables better pathogen elimination but leaves females more predisposed to autoimmune diseases. Unfortunately, the underlying basis for sex-specific immune responses remains poorly understood. Here, we show a sex difference in the CD8+ T cell response to an enteric virus, Coxsackievirus B3 (CVB3). We found that CVB3 induced expansion of CD8+ T cells in female mice but not in male mice. CVB3 also increased the proportion and number of CD11ahiCD62Llo CD8+ T cells in female mice, indicative of activation. This response was independent of the inoculation route and type I interferon. Using a recombinant CVB3 virus expressing a model CD8+ T cell epitope, we found that the expansion of CD8+ T cells in females is viral-specific and not due to bystander activation. Finally, the depletion of CD8+ T cells, prior to infection, led to enhanced mortality, indicating that CD8+ T cells are protective against CVB3 in female mice. These data demonstrate that CVB3 induces a CD8+ T cell response in female mice and highlight the importance of sex-specific immune responses to viral pathogens.
SARS‐CoV‐2 infection of polarized human airway epithelium induces necroptosis that causes airway epithelial barrier dysfunction

Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) is the cause the ongoing pandemic of coronavirus disease 2019 (COVID19). One key feature associated with COVID‐19 is excessive pro‐inflammatory cytokine production that leads to severe acute respiratory distress syndrome. Although the cytokine storm induces inflammatory cell death in the host, which type of programmed cell death mechanism that occurs in various organs and cells remains elusive. Using an in vitro culture model of polarized human airway epithelium (HAE), we observed that necroptosis, but not apoptosis or pyroptosis, plays an essential role in the damage of the epithelial barrier of polarized HAE infected with SARS‐CoV‐2. Pharmacological inhibitors of necroptosis, necrostatin‐2 and necrosulfonamide, efficiently prevented cell death and epithelial barrier dysfunction caused by SARS‐CoV‐2 infection. Moreover, the silencing of genes that are involved in necroptosis, RIPK1, RIPK3, and MLKL, ameliorated airway epithelial damage of the polarized HAE infected with SARS‐CoV‐2. This study, for the first time, confirms that SARS‐CoV‐2 infection triggers necroptosis that disrupts the barrier function of human airway epithelia in vitro.
Induction of Fungal Secondary Metabolites by Co-Culture with Actinomycete Producing HDAC Inhibitor Trichostatins

A recently bioinformatic analysis of genomic sequences of fungi indicated that fungi are able to produce more secondary metabolites than expected. Despite their potency, many biosynthetic pathways are silent in the absence of specific culture conditions or chemical cues. To access cryptic metabolism, 108 fungal strains isolated from various sites were cultured with or without Streptomyces sp. 13F051 which mainly produces trichostatin analogues, followed by comparison of metabolic profiles using LC-MS. Among the 108 fungal strains, 14 produced secondary metabolites that were not recognized or were scarcely produced in mono-cultivation. Of these two fungal strains, Myrmecridium schulzeri 15F098 and Scleroconidioma sphagnicola 15S058 produced four new compounds (1-4) along with a known compound (5), demonstrating that all four compounds were produced by physical interaction with Streptomyces sp. 13F051. Bioactivity evaluation indicated that compounds 3-5 impede migration of MDA-MB-231 breast cancer cells.
Comparison of the Choroid in Primary Open Angle and Angle Closure Glaucoma Using Optical Coherence Tomography

Précis: The current study highlights distinct choroidal alterations in primary open angle (POAG) and primary angle closure (PACG) glaucomas, underscoring the potential of the Choroidal Vascularity Index (CVI) as a valuable indicator for understanding glaucoma pathogenesis. Purpose: To evaluate choroidal structural changes in patients with POAG and PACG and healthy controls utilizing the CVI and subfoveal choroidal thickness by enhanced depth imaging optical coherence tomography. Methods: This study was cross-sectional. A total of 171 eyes of 171 subjects, comprising 69 eyes with untreated POAG, 58 eyes with untreated PACG, and 44 healthy eyes, were enrolled in this study. Subfoveal choroidal thickness, luminal area (LA), stromal area (SA), and total choroidal area were measured on enhanced depth imaging–optical coherence tomography scans. The CVI parameter is calculated as the proportion of LA to the total choroidal area. Results: This study included 69 patients with POAG with a mean age of 51.4 ± 13.3 years, 58 patients with PACG with a mean age of 57.0 ± 7.3 years, and 44 healthy subjects with a mean age of 51.11 ± 10.7 years. The CVI in the POAG and PACG groups was significantly lower than that in the control group (P = 0.001 and P = 0.005, respectively); however, not significantly different between the two glaucoma groups (P = 1.000). POAG eyes had significantly lower LA than PACG and controls (P = 0.014 and P = 0.049, respectively), whereas PACG eyes had significantly greater SA than controls (P = 0.041). Conclusions: The CVI of POAG and PACG eyes was significantly lower than that of normal eyes. A reduced LA was observed mainly in eyes with POAG, and an increased SA was observed mainly in eyes with PACG. The role of the choroid may differ between POAG and PACG eyes.
On the Challenges of Building Datasets for Hate Speech Detection

Detection of hate speech has been formulated as a standalone application of NLP and different approaches have been adopted for identifying the target groups, obtaining raw data, defining the labeling process, choosing the detection algorithm, and evaluating the performance in the desired setting. However, unlike other downstream tasks, hate speech suffers from the lack of large-sized, carefully curated, generalizable datasets owing to the highly subjective nature of the task. In this paper, we first analyze the issues surrounding hate speech detection through a data-centric lens. We then outline a holistic framework to encapsulate the data creation pipeline across seven broad dimensions by taking the specific example of hate speech towards sexual minorities. We posit that practitioners would benefit from following this framework as a form of best practice when creating hate speech datasets in the future.
Gravitational waves in New General Relativity

The models of New General Relativity have recently got attention of research community, and there are some works studying their dynamical properties. The formal aspects of this investigation have been mostly restricted to the primary constraints in the Hamiltonian analysis. However, it is by far not enough for counting their degrees of freedom or judging whether they are any good and viable. In this paper we study linearised equations in vacuum around the trivial Minkowski tetrad. By taking the approach of cosmological perturbation theory we show that the numbers of primary constraints are very easily seen without any need of genuine Hamiltonian techniques, and give the full count of linearised degrees of freedom in the weak field limit of each and every version of New General Relativity without matter.
A Critical Review of Common Log Data Sets Used for Evaluation of Sequence-based Anomaly Detection Techniques

Log data store event execution patterns that correspond to underlying workflows of systems or applications. While most logs are informative, log data also include artifacts that indicate failures or incidents. Accordingly, log data are often used to evaluate anomaly detection techniques that aim to automatically disclose unexpected or otherwise relevant system behavior patterns. Recently, detection approaches leveraging deep learning have increasingly focused on anomalies that manifest as changes of sequential patterns within otherwise normal event traces. Several publicly available data sets, such as HDFS, BGL, Thunderbird, OpenStack, and Hadoop, have since become standards for evaluating these anomaly detection techniques, however, the appropriateness of these data sets has not been closely investigated in the past. In this paper we therefore analyze six publicly available log data sets with focus on the manifestations of anomalies and simple techniques for their detection. Our findings suggest that most anomalies are not directly related to sequential manifestations and that advanced detection techniques are not required to achieve high detection rates on these data sets.
Pre-and Post-Contact Policy Decomposition for Non-Prehensile Manipulation with Zero-Shot Sim-To-Real Transfer

We present a system for non-prehensile manipulation that require a significant number of contact mode transitions and the use of environmental contacts to successfully manipulate an object to a target location. Our method is based on deep reinforcement learning which, unlike state-of-the-art planning algorithms, does not require apriori knowledge of the physical parameters of the object or environment such as friction coefficients or centers of mass. The planning time is reduced to the simple feed-forward prediction time on a neural network. We propose a computational structure, action space design, and curriculum learning scheme that facilitates efficient exploration and sim-to-real transfer. In challenging real-world non-prehensile manipulation tasks, we show that our method can generalize over different objects, and succeed even for novel objects not seen during training. Project website: https://sites.google. com/view/nonprenehsile-decomposition
The Best Arm Evades: Near-optimal Multi-pass Streaming Lower Bounds for Pure Exploration in Multi-armed Bandits

We give a near-optimal sample-pass trade-off for pure exploration in multi-armed bandits (MABs) via multi-pass streaming algorithms: any streaming algorithm with sublinear memory that uses the optimal sample complexity of $O(\frac{n}{\Delta^2})$ requires $\Omega(\frac{\log{(1/\Delta)}}{\log\log{(1/\Delta)}})$ passes. Here, $n$ is the number of arms and $\Delta$ is the reward gap between the best and the second-best arms. Our result matches the $O(\log(\frac{1}{\Delta}))$-pass algorithm of Jin et al. [ICML'21] (up to lower order terms) that only uses $O(1)$ memory and answers an open question posed by Assadi and Wang [STOC'20].
The Faraday Effect and Phase Transition in the CH3NH3PbI3 Halide Perovskite Single Crystal

The spin degree of freedom of charge carriers in halide‐perovskite semiconductors can be highly useful for information photonics applications. The Faraday effect is known to be the best indicator of paramagnetism of the material and of the spin‐light interaction. In this work, the Faraday effect is demonstrated, for the first time, in a hybrid organic–inorganic halide perovskite MAPbI3 (MA+ = CH3NH). The Faraday rotation and birefringence are measured across the tetragonal‐cubic phase transition at 327 K. The Faraday rotation is strongly suppressed below the phase transition temperature due to anisotropy (linear birefringence) of the tetragonal crystal phase. The situation changes drastically above the phase transition temperature, when the crystal becomes optically isotropic. The emerging Faraday rotation obeys the Curie law, demonstrating its population‐related paramagnetic nature. This observation opens new prospects for application of these systems and for their investigations using methods of the polarization noise spectroscopy applicable to optically anisotropic materials.
On the Minimax Regret in Online Ranking with Top-k Feedback

In online ranking, a learning algorithm sequentially ranks a set of items and receives feedback on its ranking in the form of relevance scores. Since obtaining relevance scores typically involves human annotation, it is of great interest to consider a partial feedback setting where feedback is restricted to the top-$k$ items in the rankings. Chaudhuri and Tewari [2017] developed a framework to analyze online ranking algorithms with top $k$ feedback. A key element in their work was the use of techniques from partial monitoring. In this paper, we further investigate online ranking with top $k$ feedback and solve some open problems posed by Chaudhuri and Tewari [2017]. We provide a full characterization of minimax regret rates with the top $k$ feedback model for all $k$ and for the following ranking performance measures: Pairwise Loss, Discounted Cumulative Gain, and Precision@n. In addition, we give an efficient algorithm that achieves the minimax regret rate for Precision@n.
Monotone Tree-Based GAMI Models by Adapting XGBoost

Recent papers have used machine learning architecture to fit low-order functional ANOVA models with main effects and second-order interactions. These GAMI (GAM + Interaction) models are directly interpretable as the functional main effects and interactions can be easily plotted and visualized. Unfortunately, it is not easy to incorporate the monotonicity requirement into the existing GAMI models based on boosted trees, such as EBM (Lou et al. 2013) and GAMI-Lin-T (Hu et al. 2022). This paper considers models of the form $f(x)=\sum_{j,k}f_{j,k}(x_j, x_k)$ and develops monotone tree-based GAMI models, called monotone GAMI-Tree, by adapting the XGBoost algorithm. It is straightforward to fit a monotone model to $f(x)$ using the options in XGBoost. However, the fitted model is still a black box. We take a different approach: i) use a filtering technique to determine the important interactions, ii) fit a monotone XGBoost algorithm with the selected interactions, and finally iii) parse and purify the results to get a monotone GAMI model. Simulated datasets are used to demonstrate the behaviors of mono-GAMI-Tree and EBM, both of which use piecewise constant fits. Note that the monotonicity requirement is for the full model. Under certain situations, the main effects will also be monotone. But, as seen in the examples, the interactions will not be monotone.
On the Effects of Heterogeneous Errors on Multi-fidelity Bayesian Optimization

Bayesian optimization (BO) is a sequential optimization strategy that is increasingly employed in a wide range of areas including materials design. In real world applications, acquiring high-fidelity (HF) data through physical experiments or HF simulations is the major cost component of BO. To alleviate this bottleneck, multi-fidelity (MF) methods are used to forgo the sole reliance on the expensive HF data and reduce the sampling costs by querying inexpensive low-fidelity (LF) sources whose data are correlated with HF samples. However, existing multi-fidelity BO (MFBO) methods operate under the following two assumptions that rarely hold in practical applications: (1) LF sources provide data that are well correlated with the HF data on a global scale, and (2) a single random process can model the noise in the fused data. These assumptions dramatically reduce the performance of MFBO when LF sources are only locally correlated with the HF source or when the noise variance varies across the data sources. In this paper, we dispense with these incorrect assumptions by proposing an MF emulation method that (1) learns a noise model for each data source, and (2) enables MFBO to leverage highly biased LF sources which are only locally correlated with the HF source. We illustrate the performance of our method through analytical examples and engineering problems on materials design.
STATE-OF-ART Algorithms for Injectivity and Bounded Surjectivity of One-dimensional Cellular Automata

Surjectivity and injectivity are the most fundamental problems in cellular automata (CA). We simplify and modify Amoroso's algorithm into optimum and make it compatible with fixed, periodic and reflective boundaries. A new algorithm (injectivity tree algorithm) for injectivity is also proposed. After our theoretic analysis and experiments, our algorithm for injectivity can save much space and 90\% or even more time compared with Amoroso's algorithm for injectivity so that it can support the decision of CA with larger neighborhood sizes. At last, we prove that the reversibility with the periodic boundary and global injectivity of one-dimensional CA is equivalent.
Fairness of Exposure in Dynamic Recommendation

Exposure bias is a well-known issue in recommender systems where the exposure is not fairly distributed among items in the recommendation results. This is especially problematic when bias is amplified over time as a few items (e.g., popular ones) are repeatedly over-represented in recommendation lists and users' interactions with those items will amplify bias towards those items over time resulting in a feedback loop. This issue has been extensively studied in the literature in static recommendation environment where a single round of recommendation result is processed to improve the exposure fairness. However, less work has been done on addressing exposure bias in a dynamic recommendation setting where the system is operating over time, the recommendation model and the input data are dynamically updated with ongoing user feedback on recommended items at each round. In this paper, we study exposure bias in a dynamic recommendation setting. Our goal is to show that existing bias mitigation methods that are designed to operate in a static recommendation setting are unable to satisfy fairness of exposure for items in long run. In particular, we empirically study one of these methods and show that repeatedly applying this method fails to fairly distribute exposure among items in long run. To address this limitation, we show how this method can be adapted to effectively operate in a dynamic recommendation setting and achieve exposure fairness for items in long run. Experiments on a real-world dataset confirm that our solution is superior in achieving long-term exposure fairness for the items while maintaining the recommendation accuracy.