Miracle-dz/UniFAR-FTUs huggingface dataset:
Mechanism of feature learning in deep fully connected networks and kernel machines that recursively learn features

In recent years neural networks have achieved impressive results on many technological and scientific tasks. Yet, the mechanism through which these models automatically select features, or patterns in data, for prediction remains unclear. Identifying such a mechanism is key to advancing performance and interpretability of neural networks and promoting reliable adoption of these models in scientific applications. In this paper, we identify and characterize the mechanism through which deep fully connected neural networks learn features. We posit the Deep Neural Feature Ansatz, which states that neural feature learning occurs by implementing the average gradient outer product to up-weight features strongly related to model output. Our ansatz sheds light on various deep learning phenomena including emergence of spurious features and simplicity biases and how pruning networks can increase performance, the"lottery ticket hypothesis. "Moreover, the mechanism identified in our work leads to a backpropagation-free method for feature learning with any machine learning model. To demonstrate the effectiveness of this feature learning mechanism, we use it to enable feature learning in classical, non-feature learning models known as kernel machines and show that the resulting models, which we refer to as Recursive Feature Machines, achieve state-of-the-art performance on tabular data.
Non-Strict Plurisubharmonicity of Energy on Teichmüller Space

For an irreducible representation $\rho :\pi _{1}(\Sigma _{g})\to \textrm {GL}(n,\mathbb {C})$, there is an energy functional $\textrm {E}_{\rho }: {{\mathcal {T}}}_{g}\to \mathbb {R}$, defined on Teichmüller space by taking the energy of the associated equivariant harmonic map into the symmetric space $\textrm {GL}(n,\mathbb {C})/\textrm {U}(n)$. It follows from a result of Toledo that $\textrm {E}_{\rho }$ is plurisubharmonic, that is, its Levi form is positive semi-definite. We describe the kernel of this Levi form, and relate it to the $\mathbb {C}^{*}$ action on the moduli space of Higgs bundles. We also show that the points in $ {{\mathcal {T}}}_{g}$ where strict plurisubharmonicity fails (i.e., this kernel is non-zero) are critical points of the Hitchin fibration. When $n\geq 2$ and $g\geq 3$, we show that for a generic choice $(S,\rho )$, the map $\textrm {E}_{\rho }$ is strictly plurisubharmonic. We also describe the kernel of the Levi form for $n=1$.
Low genetic heterogeneity of Leishmania major in different geographical regions of Iran

To examine the genetic diversity of Leishmania major, 100 Giemsa-stained positive slides were collected from endemic foci of Iran (Northeast, Central, and Southwest provinces) over two consecutive years during 2019–2021. The Leishmania ITS-rDNA gene was amplified and Leishmania sp. was recognized by PCR-RFLP and sequencing. In addition, 178 registered ITS-rDNA sequences from other geographical regions of Iran were retrieved from GenBank, including different host species (human, sandfly and rodent). A total of 40 new haplotypes were discovered using the ITS-rDNA sequence analysis. IR29 (20.6%) and IR34 (61%) were the two most common haplotypes, represented by a star-like feature in the overall population. Analysis of the molecular variance test revealed low genetic diversity of L. major in human cases (Haplotype diversity; 0.341), rodent (Hd; 0.387) and sandfly (Hd; 0.390) sequences. The lowest genetic diversity of L. major was observed in Southwest/Southeast Iran (Hd: 0.104–0.286). The statistically Fst value indicated that L. major is not genetically differentiated between geographic regions of Iran, except for the Northeast-Southwest (Fst: 0.29055) and Central-Southwest (Fst: 0.30294) population pairs. The current study as the first investigation discloses new perspectives for further evaluation in the identification local transmission paradigms and initiating effective prevention strategies.
A protocol for a multi-site cohort study to evaluate child and adolescent mental health service transformation in England using the i-THRIVE model

The National i-THRIVE Programme seeks to evaluate the impact of the NHS England-funded whole system transformation on child and adolescent mental health services (CAMHS). This article reports on the design for a model of implementation that has been applied in CAMHS across over 70 areas in England using the ‘THRIVE’ needs-based principles of care. The implementation protocol in which this model, ‘i-THRIVE’ (implementing-THRIVE), will be used to evaluate the effectiveness of the THRIVE intervention is reported, together with the evaluation protocol for the process of implementation. To evaluate the effectiveness of i-THRIVE to improve care for children and young people’s mental health, a cohort study design will be conducted. N = 10 CAMHS sites that adopt the i-THRIVE model from the start of the NHS England-funded CAMHS transformation will be compared to N = 10 ‘comparator sites’ that choose to use different transformation approaches within the same timeframe. Sites will be matched on population size, urbanicity, funding, level of deprivation and expected prevalence of mental health care needs. To evaluate the process of implementation, a mixed-methods approach will be conducted to explore the moderating effects of context, fidelity, dose, pathway structure and reach on clinical and service level outcomes. This study addresses a unique opportunity to inform the ongoing national transformation of CAMHS with evidence about a popular new model for delivering children and young people’s mental health care, as well as a new implementation approach to support whole system transformation. If the outcomes reflect benefit from i-THRIVE, this study has the potential to guide significant improvements in CAMHS by providing a more integrated, needs-led service model that increases access and involvement of patients with services and in the care they receive.
A Progressive Transductive Inference Algorithm Based on Support Vector Machine

Support vector machine is a new learning method developed in recent years based on the foundations of statistical learning theory. It is gaining popularity due to many attractive features and promising empirical performance in the fields of nonlinear and high dimensional pattern recognition. TSVM (transductive support vector machine) takes into account a particular test set and tries to minimize misclassifications of just those particular examples. Compared with traditional inductive support vector machines, TSVM is often more practical and can give results with better performance. In this paper, a progressive transductive support vector machine is devised and the experimental results show that the algorithm is very promising on a mixed training set of a small number of unlabeled examples and a large number of labeled examples.
Through the looking glass: the neural basis of self-concept in young adults with antisocial trajectories

Abstract Self-concept is shaped by social experiences, but it is not yet well understood how the neural and behavioral development of self-concept is influenced by a history of antisocial behavior. In this pre-registered study, we examined neural responses to self-evaluations in young adults who engaged with antisocial behavior in childhood and either desisted or persisted in antisocial behavior. A self-concept task was performed by 94 young adults (age range 18–30 years). During the task, participants with a persistent or desistent antisocial trajectory (n = 54) and typically developing young adults (n = 40) rated whether positive and negative traits in different domains (prosocial and physical) described themselves. We examined both the effects of a history of antisocial behavior as well as current heterogeneity in psychopathic traits on self-concept appraisal and its neural underpinnings. Participants endorsed more positive trait statements than negative across domains, which did not differ between antisocial-history groups. However, current psychopathic traits were negatively associated with prosocial self-concept and medial prefrontal cortex activity during self-evaluation. Together, these findings suggest that antisocial tendencies might indeed be reflected in self-concept development of young adults, specifically in the prosocial domain.
Effects of hepatocyte growth factor on porcine mammary cell growth and senescence

Background The porcine mammary glands share morphological and physiological similarities with human ones, making primary porcine mammary cells (PMC) suitable for biomedical research and a potential cellular therapeutic for breast cancer xenogeneic cell immunotherapy. Primary cells isolated from tissues remain the physiological functions of origin tissues but their self-renewal ability is restricted and cells acquire senescence during in vitro expansion. To overcome these drawbacks, here we sought to establish an approach to efficiently increase PMC’s in vitro growth. We studied the effects of the hepatocyte growth factor (HGF) to maintain the expansion capacity of porcine mammary cells and identify the possible mechanisms. Purpose HGF could allow for the increase in vitro proliferation capacity of primary epithelial cells isolated from tissue samples. To effectively produce cells for biomedical research and xenogeneic cell therapy, we planned to study the effects of HGF and its potential mechanisms of action to stimulate cell growth for PMC expansion. Methods After HGF treatment, the growth, cell cycle, senescence and the cell marker gene expression of PMCs were analyzed in standard 10% FBS and low serum 1% FBS containing medium. Results HGF significantly enhanced the cell proliferation by shifting the cell cycle population from G1 phase into S phase to increase cell division, reduced the senescent cells and reprogrammed gene expression profiles. Conclusion We demonstrated that HGF could maintain the expansion capacity of PMCs by increasing cell growth and anti-senescence capability, suggesting its potential application in optimizing the long-term culture of primary cells. Adding a specific growth factor such as HGF in culture allows enhanced expansion of heterogeneous cell populations from normal porcine mammary glandular tissues in vitro. We believe that this cell culture approach will efficiently provide cells for studying mammary cell function and supply cells for therapeutic uses.
Estimating the population prevalence and force of infection directly from antibody titres

The use of threshold values in order to diagnose individual subjects as being ‘susceptible’ or ‘infected or recovered/immune’ for a specific infection is virtually always prone to false positive, false negative or inconclusive classifications. Such misclassifications might lead to biased estimates for epidemiological parameters, such as the prevalence and the force of infection. In this article, we propose to estimate these epidemiological parameters directly from antibody titres, using an underlying mixture model. The method is applied to estimate the Salmonella serological prevalence in pigs and the age-dependent force of infection using serological data on the Varicella-Zoster virus (VZV) in humans. The threshold and direct method are compared through a simulation study.
Isometric rigidity of the Wasserstein space $\mathcal{W}_1(\mathbf{G})$ over Carnot groups

This paper aims to study isometries of the $1$-Wasserstein space $\mathcal{W}_1(\mathbf{G})$ over Carnot groups endowed with horizontally strictly convex norms. Well-known examples of horizontally strictly convex norms on Carnot groups are the Heisenberg group $\mathbb{H}^n$ endowed with the Heisenberg-Kor\'anyi norm, or with the Naor-Lee norm; and $H$-type Iwasawa groups endowed with a Kor\'anyi-type norm. We prove that on a general Carnot group there always exists a horizontally strictly convex norm. The main result of the paper says that if $(\mathbf{G},N_{\mathbf{G}})$ is a Carnot group where $N_{\mathbf{G}}$ is a horizontally strictly convex norm on $\mathbf{G}$, then the Wasserstein space $\mathcal{W}_1(\mathbf{G})$ is isometrically rigid. That is, for every isometry $\Phi:\mathcal{W}_1(\mathbf{G})\to\mathcal{W}_1(\mathbf{G})$ there exists an isometry $\psi:\mathbf{G}\to \mathbf{G}$ such that $\Phi=\psi_{\#}$.
Detection and verification of neurodegeneration after traumatic brain injury in the mouse: Immunohistochemical staining for amyloid precursor protein

Previous studies of human traumatic brain injury (TBI) have shown diffuse axonal injury as varicosities or spheroids in white matter (WM) bundles when using immunoperoxidase‐ABC staining with 22C11, a mouse monoclonal antibody against amyloid precursor protein (APP). These findings have been interpreted as TBI‐induced axonal pathology. In a mouse model of TBI however, when we used immunofluorescent staining with 22C11, as opposed to immunoperoxidase staining, we did not observe varicosities or spheroids. To explore this discrepancy, we performed immunofluorescent staining with Y188, an APP knockout‐validated rabbit monoclonal that shows baseline immunoreactivity in neurons and oligodendrocytes of non‐injured mice, with some arranged‐like varicosities. In gray matter after injury, Y188 intensely stained axonal blebs. In WM, we encountered large patches of heavily stained puncta, heterogeneous in size. Scattered axonal blebs were also identified among these Y188‐stained puncta. To assess the neuronal origin of Y188 staining after TBI we made use of transgenic mice with fluorescently labeled neurons and axons. A close correlation was observed between Y188‐stained axonal blebs and fluorescently labeled neuronal cell bodies/axons. By contrast, no correlation was observed between Y188‐stained puncta and fluorescent axons in WM, suggesting that these puncta in WM did not originate from axons, and casting further doubt on the nature of previous reports with 22C11. As such, we strongly recommend Y188 as a biomarker for detecting damaged neurons and axons after TBI. With Y188, stained axonal blebs likely represent acute axonal truncations that may lead to death of the parent neurons. Y188‐stained puncta in WM may indicate damaged oligodendrocytes, whose death and clearance can result in secondary demyelination and Wallerian degeneration of axons. We also provide evidence suggesting that 22C11‐stained varicosities or spheroids previously reported in TBI patients might be showing damaged oligodendrocytes, due to a cross‐reaction between the ABC kit and upregulated endogenous biotin.
External Field Free Spin Hall Effect Device for Perpendicular Magnetization Reversal Using a Composite Structure with Biasing Layer

In this paper, a new material structure is proposed that utilizes the spin Hall effect to switch perpendicularly magnetized materials in the absence of any externally applied field. The structure consists of a multilayered material stack including a magnetic layer with perpendicular magnetic anisotropy that serves as the storage layer and a magnetic layer with in-plane magnetic anisotropy that assists switching of the magnetization of the storage layer through stray fields. We develop a composite structure of substrate / Ta (5 nm) / CoFeB (1.2 nm) / MgO (2 nm) / CoFeB (3 nm) / MgO (2 nm) and demonstrate the spin Hall effect arising from the Ta spin orbit channel can switch the magnetization of CoFeB (1.2 nm) with perpendicular magnetic anisotropy. This new composite structure could enable more widespread use of the spin Hall effect for memory and logic applications.
Numerical Simulation of Magnetic Field Distribution Characteristics of the Four-electrode Electromagnetic Flowmeter

The magnetic field distribution of the four-electrode electromagnetic flowmeter was studied by using the numerical simulation approach.We use the finite element analysis technique to calculate the magnetic field distribution characteristics,and investigate the weight function distribution.The effect of flowmeter eccentricity and the change of magnetic permeability of the fluid on the magnetic field distribution was analyzed.This study provides theoretical analysis foundation for better understanding the measurement characteristic of electromagnetic flowmeter and points out that the finite element analysis technique is the good way to analyze the measurement characteristics of electromagnetic flowmeter.
Effect of hyperthermic intraperitoneal chemotherapy on survival and recurrence rates in advanced gastric cancer: a systematic review and meta-analysis

Background: Around 5–20% of patients who undergo surgery for advanced gastric cancer (AGC), which invades into the muscularis propria or beyond, have peritoneal carcinomatosis. The peritoneal recurrence rate is 10–54%, which is associated with a poor prognosis. The role of hyperthermic intraperitoneal chemotherapy (HIPEC) in AGC with and without peritoneal carcinomatosis is not clearly defined. Methods: The authors conducted a meta-analysis, in accordance with the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines, of the clinical trials and high-quality nonrandomized studies evaluating the role of HIPEC in AGC over the last 10 years. The studies were searched in PubMed, EMBASE, MEDLINE, and Cochrane databases between January 2011 to December 2021. Clinical data including overall survival, recurrence free survival, overall recurrence rate, peritoneal recurrence rate, and complications analyzed using RevMan 5.4. Results: Six randomized controlled trials and 10 nonrandomized studies, comprising a total of 1700 patients were included. HIPEC was associated with significantly improved OS at 3 [odd ratio (OR) 1.89, 95% CI: 1.17–3.05] and 5 years (OR 1.87, 95% CI: 1.29–2.71). HIPEC was associated with reduced overall recurrence (OR 0.49, 95% CI: 0.31–0.80) and peritoneal recurrence (OR 0.22, 95% CI: 0.11–0.47). HIPEC was not associated with increased complications. The occurrence of postoperative renal dysfunction was significantly higher in the HIPEC group (OR 3.94, 95% CI: 1.85–8.38). Conclusion: The role of HIPEC in AGC has evolved over the past decade. HIPEC may improve survival rates and reduce recurrence rates in patients with AGC, without significant increase in complications and with a favorable impact on 3 and 5-year survival.
Continuous positive airway pressure increases CSF flow and glymphatic transport

Respiration can positively influence cerebrospinal fluid (CSF) flow in the brain, yet its effects on central nervous system (CNS) fluid homeostasis, including waste clearance function via glymphatic and meningeal lymphatic systems, remain unclear. Here, we investigated the effect of supporting respiratory function via continuous positive airway pressure (CPAP) on glymphatic-lymphatic function in spontaneously breathing anesthetized rodents. To do this, we used a systems approach combining engineering, MRI, computational fluid dynamics analysis, and physiological testing. We first designed a nasal CPAP device for use in the rat and demonstrated that it functioned similarly to clinical devices, as evidenced by its ability to open the upper airway, augment end-expiratory lung volume, and improve arterial oxygenation. We further showed that CPAP increased CSF flow speed at the skull base and augmented glymphatic transport regionally. The CPAP-induced augmented CSF flow speed was associated with an increase in intracranial pressure (ICP), including the ICP waveform pulse amplitude. We suggest that the augmented pulse amplitude with CPAP underlies the increase in CSF bulk flow and glymphatic transport. Our results provide insights into the functional crosstalk at the pulmonary-CSF interface and suggest that CPAP might have therapeutic benefit for sustaining glymphatic-lymphatic function.
Comparing translational success rates across medical research fields - A combined analysis of literature and clinical trial data.

Many interventions that show promising results in preclinical development do not pass clinical tests. Part of this may be explained by poor animal-to-human translation. Using animal models with low predictability for humans is neither ethical, nor efficient. If translational success shows variation between medical research fields, analyses of common practices in these fields could identify factors contributing to successful translation. We have thus assessed translational success rates in medical research fields using two approaches: through literature and clinical trial registers. Literature: We comprehensively searched PubMed for pharmacology, neuroscience, cancer research, animal models, clinical trials, and translation. After screening, 117 review papers were included in this scoping review. Translational success rates were not different within pharmacology (72%), neuroscience (62%) and cancer research (69%). Clinical trials: The fraction of phase-2 clinical trials with a positive outcome was used as a proxy (i.e., an indirect resemblance measure) for translational success. Trials were retrieved from the WHO trial register and categorized into medical research fields following the international classification of disease (ICD-10). Of the phase-2 trials analyzed, 65.2% were successful. Fields with the highest success rates were disorders of lipoprotein metabolism (86.0%) and epilepsy (85.0%). Fields with the lowest success rates were schizophrenia (45.4%) and pancreatic cancer (46.0%). Our combined analyses suggest relevant differences in success rates between medical research fields. Based on the clinical trials, comparisons of practice between, e.g., epilepsy and schizophrenia might identify factors that could influence translational success.