Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Domain-Agnostic Representation for Disease Diagnosis

In clinical environments, image-based diagnosis is desired to achieve robustness on multi-center samples. Toward this goal, a natural way is to capture only clinically disease-related features. However, such disease-related features are often entangled with center-effect, disabling robust transferring to unseen centers/domains. To disentangle disease-related features, we first leverage structural causal modeling to explicitly model disease-related and center-effects that are provable to be disentangled from each other. Guided by this, we propose a novel Domain Agnostic Representation Model (DarMo) based on variational Auto-Encoder. To facilitate disentanglement, we design domain-agnostic and domain-aware encoders to respectively capture disease-related features and varied center effects by incorporating a domain-aware batch normalization layer. Besides, we constrain the disease-related features to well predict the disease label as well as clinical attributes, by leveraging Graph Convolutional Network (GCN) into our decoder. The effectiveness and utility of our method are demonstrated by the superior performance over others on both public datasets and in-house datasets.
A Simple Low-Cost Method to Prepare Lignocellulose-Based Composites for Efficient Removal of Cd(II) from Wastewater

The fabrication of functional lignocellulose-based materials has drawn considerable attention because it acts as a green separation/absorption material owing to its multi-porous mesostructure. In this study, a surface functionalized lignocellulose-based adsorbent for the highly efficient capture of Cd(II) ions was prepared through facile in situ co-deposition of wood waste-derived saw powder (SP) in the presence of tannic acid (TA) and aminopropyltriethoxysilane (APTES) mixed aqueous solution. The SP was first modified using TA-APTES coating to synthesize the functional SP substrate (SP-(TA-APTES)). The SP-(TA-APTES) hybrids served as reactive platforms, which enabled further decoration with amino-rich polyethylenimine (PEI) due to the outstanding secondary reactions of the TA-APTES layer. The surface morphology of the resulting SP-(TA-APTES)-PEI (SP-TAPI) composites were investigated using Fourier-transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), X-ray diffraction (XRD), thermogravimetric analysis (TGA), and scanning electron microscopy (SEM). Significantly, the combined advantages of the lignocellulosic skeleton, the layer-particle structure, and the hybrid coating contributed to the enhanced adsorption capacity of Cd(II) (up to 22.66 mg/g at pH = 5.0). This removal capacity was higher than that of most reported agricultural waste-based or lignocellulose-based materials. The Cd(II) adsorption mechanism of the surface-modified SP-TAPI composites was studied in detail. These results provide new insights into the high value-added utilization of agricultural waste for water purification applications.
A Quantitative Version of Simple Types

This work introduces a quantitative version of the simple type assignment system, starting from a suitable restriction of non-idempotent intersection types. The resulting system is decidable and has the same typability power as the simple type system; thus, assigning types to terms supplies the very same qualitative information given by simple types, but at the same time can provide some interesting quantitative information. It is well known that typability for simple types is equivalent to unification; we prove a similar result for the newly introduced system. More precisely, we show that typability is equivalent to a unification problem which is a non-trivial extension of the classical one: in addition to unification rules, our typing algorithm makes use of an expansion operation that increases the cardinality of multisets whenever needed.
Production of Mesenchymal Stem Cells through Stem Cell Reprogramming

Mesenchymal stem cells (MSCs) possess a broad spectrum of therapeutic applications and have been used in clinical trials. MSCs are mainly retrieved from adult or fetal tissues. However, there are many obstacles with the use of tissue-derived MSCs, such as shortages of tissue sources, difficult and invasive retrieval methods, cell population heterogeneity, low purity, cell senescence, and loss of pluripotency and proliferative capacities over continuous passages. Therefore, other methods to obtain high-quality MSCs need to be developed to overcome the limitations of tissue-derived MSCs. Pluripotent stem cells (PSCs), including embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs), are considered potent sources for the derivation of MSCs. PSC-derived MSCs (PSC-MSCs) may surpass tissue-derived MSCs in proliferation capacity, immunomodulatory activity, and in vivo therapeutic applications. In this review, we will discuss basic as well as recent protocols for the production of PSC-MSCs and their in vitro and in vivo therapeutic efficacies. A better understanding of the current advances in the production of PSC-MSCs will inspire scientists to devise more efficient differentiation methods that will be a breakthrough in the clinical application of PSC-MSCs.
Development of Acoustic Emission Sensor Optimized for Partial Discharge Monitoring in Power Transformers

The acoustic emission (AE) technique is one of the unconventional methods of partial discharges (PD) detection. It plays a particularly important role in oil-filled power transformers diagnostics because it enables the detection and online monitoring of PDs as well as localization of their sources. The performance of this technique highly depends on measurement system configuration but mostly on the type of applied AE sensor. The paper presents, in detail, the design and manufacturing stages of an ultrasensitive AE sensor optimized for partial discharge detection in power transformers. The design assumptions were formulated based on extensive laboratory research, which allowed for the identification of dominant acoustic frequencies emitted by partial discharges in oil–paper insulation. The Krimholtz–Leedom–Matthaei (KLM) model was used to iteratively find optimal material and geometric properties of the main structures of the prototype AE sensor. It has two sensing elements with opposite polarization direction and different heights. The fully differential design allowed to obtain the desired properties of the transducer, i.e., a two-resonant (68 kHz and 90 kHz) and wide (30–100 kHz) frequency response curve, high peak sensitivity (−61.1 dB ref. V/µbar), and low noise. The laboratory tests confirmed that the prototype transducer is characterized by ultrahigh sensitivity of partial discharge detection. Compared to commonly used commercial AE sensors, the average amplitude of PD pulses registered with the prototype sensor was a minimum of 5.2 dB higher, and a maximum of 19.8 dB higher.
Congo Red Fluorescence for Rapid In Situ Characterization of Synthetic Curli Systems

Curli are proteins produced by many bacteria as a structural component of biofilms, and they have recently emerged as a platform for fabrication of biological materials. Curli fibers are very robust and resistant to degradation, and the curli subunits can tolerate many protein fusions, facilitating the biosynthesis of novel functional materials. A serious bottleneck in the development of more sophisticated engineered curli systems is the rapid quantification of curli production by the bacteria. In this work we address this issue by developing a technique to monitor curli production directly in bacterial cultures, allowing for rapid curli quantification in a manner compatible with many powerful high-throughput techniques that can be used to engineer complex biological material systems. ABSTRACT Curli are amyloid proteins that are assembled into extracellular polymeric fibers by bacteria during biofilm formation. The beta-sheet-rich protein CsgA, the primary structural component of the fibers, is secreted through dedicated machinery and self-assembles into cell-anchored fibers many times longer than the cell. Here, we have developed an in situ fluorescence assay for curli production that exploits the fluorescent properties of Congo red (CR) dye when bound to amyloid, allowing for rapid and robust curli quantification. We initially evaluated three amyloid-binding dyes for the fluorescent detection of curli in bacterial culture and found only Congo red compatible with in situ quantification. We further characterized the fluorescent properties of the dye directly in bacterial culture and calibrated the fluorescence using purified CsgA protein. We then used the Congo red assay to rapidly develop and characterize inducible curli-producing constructs in both an MC4100-derived lab strain of Escherichia coli and a derivative of the probiotic strain E. coli Nissle. This technique can be used to evaluate curli production in a minimally invasive manner using a range of equipment, simplifying curli quantification and the development of novel engineered curli systems. IMPORTANCE Curli are proteins produced by many bacteria as a structural component of biofilms, and they have recently emerged as a platform for fabrication of biological materials. Curli fibers are very robust and resistant to degradation, and the curli subunits can tolerate many protein fusions, facilitating the biosynthesis of novel functional materials. A serious bottleneck in the development of more sophisticated engineered curli systems is the rapid quantification of curli production by the bacteria. In this work we address this issue by developing a technique to monitor curli production directly in bacterial cultures, allowing for rapid curli quantification in a manner compatible with many powerful high-throughput techniques that can be used to engineer complex biological material systems.
Towards Addressing Label Skews in One-Shot Federated Learning

Federated learning (FL) has been a popular research area, where multiple clients collaboratively train a model without sharing their local raw data. Among existing FL solutions, one-shot FL is a promising and challenging direction, where the clients conduct FL training with a single communication round. However, while label skew is a common real-world scenario where some clients may have few or no data of some classes, existing one-shot FL approaches that conduct voting on the local models are not able to produce effective global models. Due to the limited number of classes in each party, the local models misclassify the data from unseen classes into seen classes, which leads to very ineffective global models from voting. To address the label skew issue in one-shot FL, we propose a novel approach named FedOV which generates diverse outliers and introduces them as an additional unknown class in local training to improve the voting performance. Specifically, based on open-set recognition, we propose novel outlier generation approaches by corrupting the original features and further develop adversarial learning to enhance the outliers. Our extensive experiments show that FedOV can significantly improve the test accuracy compared to state-of-the-art approaches in various label skew settings. Code is available at https://github.com/Xtra-Computing/FedOV.
Can We Faithfully Represent Absence States to Compute Shapley Values on a DNN?

Although many methods have been proposed to estimate attributions of input variables, there still exists a significant theoretical flaw in masking-based attribution methods, i.e. it is hard to examine whether the masking method faithfully represents the absence of input variables. Specifically, for masking-based attributions, setting an input variable to the baseline value is a typical way of representing the absence of the variable. However, there are no studies investigating how to represent the absence of input variables and verify the faithfulness of baseline values. Therefore, we revisit the feature representation of a DNN in terms of causality, and propose to use causal patterns to examine whether the masking method faithfully removes information encoded in input variables. More crucially, it is proven that the causality can be explained as the elementary rationale of the Shapley value. Furthermore, we define the optimal baseline value from the perspective of causality, and we propose a method to learn the optimal baseline value. Experimental results have demonstrated the effectiveness of our method.
Learning Continuous Normalizing Flows For Faster Convergence To Target Distribution via Ascent Regularizations

Normalizing flows (NFs) have been shown to be advantageous in modeling complex distributions and improving sampling efficiency for unbiased sampling. In this work, we propose a new class of continuous NFs, ascent continuous normalizing flows (ACNFs), that makes a base distribution converge faster to a target distribution. As solving such a flow is non-trivial and barely possible, we propose a practical implementation to learn flexibly parametric ACNFs via ascent regularization and apply it in two learning cases: maximum likelihood learning for density estimation and minimizing reverse KL divergence for unbiased sampling and variational inference. The learned ACNFs demonstrate faster convergence towards the target distributions, therefore, achieving better density estimations, unbiased sampling and variational approximation at lower computational costs. Furthermore, the flows show to stabilize themselves to mitigate performance deterioration and are less sensitive to the choice of training flow length T .
Commutateurs de certains semi-groupes holomorphes et applications aux directions alternées

Soient A et B des operateurs lineaires formels qui ne commutent pas necessairement entre eux. Des formules de directions alternees d'ordre eleve sont definies au moyen de M 1 (t) = 4/3 e tA/4 e tB/2 e tA/2 e tB/2 e tA/4 - 1/3 e tA/2 e tB e tA/2 M 2 (t) = 2/3 (e tA/2 e tB e tA/2 + e tB/2 e tA e tB/2 ) - 1/6 (e tA e tB + e tB e tA ) et au sens des series formelles formule math. Si a, a 0 , b et b 0 sont des fonctions strictement positives indefiniment differentiables de T 2 = (R/Z) 2 dans R, definissons des operateurs A et B par A = ∂/∂x 1 (a(x 1 , X 2 )∂/∂x 1 ) - a 0 (x 1 , X 2 ); B = ∂/∂x 2 (b(X 1 , X 2 ) ∂/∂x 2 ) - b 0 (X 1 , X 2 ). Les operateurs A et B engendrent des semi-groupes holomorphes dans L 2 (T 2 ) et les estimations suivantes ont lieu en norme d'operateurs dans L 2 (T 2 ) ∥M 1 (t)∥ = 1 + O(t) et ∥M 2 (t)∥ = 1 + O(t). De la nous deduisons qu'il existe une constante c telle que ∥M 1 (t/n) n ∥ ≤ e ct et ∥M 2 (t/n) n ∥ ≤ e ct et donc les formules (*) sont stables.
Global social identity predicts cooperation at local, national, and global levels: Results from international experiments

Individuals who identify themselves with humanity as a whole tend to be more prosocial in a number of different domains, from giving to international charities to volunteering for humanitarian causes. In this paper, we show that global identity is “inclusive” in character. That is, rather than neglecting or diminishing attachments to local and national groups, identification with all of humanity encourages individuals to embrace local and national goals at no lesser intensity than they embrace global goals. We have done so using experimental data on social dilemmas at the local level and nested social dilemmas at the local and national level, as well as at the local and world levels. Experiments were conducted with adult samples in the United States, Italy, Russia, Argentina, South Africa, and Iran. We show that the higher the identification with global collectives, net of identification with local and national collectives, the higher the cooperation at the local, national, and world levels. Conversely, local social identity is not significantly associated with cooperation at any level of interaction, while national social identity, net of local and global identification, tends overall to have a negative correlation with cooperation, particularly at the local level. We also show that individuals with strong global identity are significantly more optimistic of others’ contributions than individuals with lower levels of global identification, but they are as accurate as others in predicting others’ cooperation at the local and national levels. Their forecast error is instead systematically larger than that of all others for cooperation at the world level.
Different effects of I-wave periodicity repetitive TMS on motor cortex interhemispheric interaction

Background Activity of the neural circuits in the human motor cortex can be probed using transcranial magnetic stimulation (TMS). Changing TMS-induced current direction recruits different cortical neural circuits. I-wave periodicity repetitive TMS (iTMS) substantially modulates motor cortex excitability through neural plasticity, yet its effect on interhemispheric interaction remains unclear. Objective To explore the modulation of interhemispheric interaction by iTMS applied in different current directions. Materials and Methods Twenty right-handed healthy young volunteers (aged 27.5 ± 5.0 years) participated in this study with three visits. On each visit, iTMS in posterior–anterior/anterior–posterior direction (PA-/AP-iTMS) or sham-iTMS was applied to the right hemisphere, with corticospinal excitability and intracortical facilitation of the non-stimulated left hemisphere evaluated at four timepoints. Ipsilateral silent period was also measured at each timepoint probing interhemispheric inhibition (IHI). Results PA- and AP-iTMS potentiated cortical excitability concurrently in the stimulated right hemisphere. Corticospinal excitability of the non-stimulated left hemisphere increased 10 min after both PA- and AP-iTMS intervention, with a decrease in short-interval intracortical facilitation (SICF) observed in AP-iTMS only. Immediately after the intervention, PA-iTMS tilted the IHI balance toward inhibiting the non-stimulated hemisphere, while AP-iTMS shifted the balance toward the opposite direction. Conclusions Our findings provide systematic evidence on the plastic modulation of interhemispheric interaction by PA- and AP-iTMS. We show that iTMS induces an interhemispheric facilitatory effect, and that PA- and AP-iTMS differs in modulating interhemispheric inhibition.
Training drills in high performance badminton—effects of interval duration on internal and external loads

Purpose: The aim of the present study was to analyze the impact of interval duration on training loads and technical skill performance in high performance badminton drills. Methods: On three experimental days, 19 internationally ranked players (13 male: 22.7 ± 3.8 years, 180 ± 6 cm, 71.5 ± 6.1 kg; 6 females: 20.4 ± 2.5 years, 168 ± 4 cm, 59.8 ± 6.0 kg) completed one of three protocols (T10, T30, and T50) of a typical badminton specific drill, the so-called “Multifeeding” (the coach feeds shuttlecock without break in a random order) in a counterbalanced order. The protocols varied in interval duration (10, 30, and 50 s) but were matched for the rally-to-rest-ratio (1:1) and active playing time (600 s). Cardiorespiratory responses (portable spirometry, chest belt), energy metabolism (levels of blood lactate, La), rate of perceived exertion (RPE), player’s kinematics (Local Positioning System), and technical skill performance (video analysis) were measured. Results: Average oxygen consumption (T10 45 ± 6; T30 46 ± 7; T50 44 ± 6 mL min−1·kg−1), Energy expenditure (886 ± 209; 919 ± 176; 870 ± 206 kcal h−1), heart rate (164 ± 13; 165 ± 11; 165 ± 10 bpm) and RPE (16 ± 2; 17 ± 2; 17 ± 2) did not differ between the protocols. Respiratory exchange ratio (RER) and La significantly increased depending on interval duration (RER: 0.90 ± 0.05; 0.93 ± 0.03; 0.96 ± 0.04 and La: 3.6 ± 2.0; 5.6 ± 3.0; 7.3 ± 2.3 mmol l−1). Stroke frequency (SF; 0.58 ± 0.05; 0.57 ± 0.05; 0.55 ± 0.06 strokes·s−1) was similar while distance covered, and average running velocity were significantly lower for T50 compared to T10 (76 ± 17; 70 ± 13; 65 ± 11 m min−1). Moreover, jump frequency in T30 was higher than in T10 (6.7 ± 3.1; 8.8 ± 3.8; 8.5 ± 4.2 jumps·min−1), whereas differences in internal and external loads were not associated with changes in stroke precision (errors: 16 ± 6; 19 ± 4; 18 ± 4%; accuracy: 22 ± 6; 24 ± 8; 23 ± 8%). Conclusion: Anaerobic metabolic stimulus increases while running distance and velocity decrease, in case of longer interval durations. Even though there was no impact on stroke precision, extending the intervals beyond 30 s might impair external training load and skill performance. Consequently, interval duration should be defined carefully depending on the training goals.
Tidewater glaciers as “climate refugia” for zooplankton-dependent food web in Kongsfjorden, Svalbard

With climate warming, many tidewater glaciers are retreating. Fresh, sediment-rich sub-glacial meltwater is discharged at the glacier grounding line, where it mixes with deep marine water resulting in an upwelling of a plume visible in front of the glacial wall. Zooplankton may suffer increased mortality within the plume due to osmotic shock when brought in contact with the rising meltwater. The constant replenishment of zooplankton and juvenile fish to the surface areas attracts surface-foraging seabirds. Because access to other feeding areas, such as the marginal ice zone, has become energetically costly due to reduced sea-ice extent, glacial plumes may become increasingly important as “climate refugia” providing enhanced prey availability. Here, we investigated zooplankton concentrations within the plume and adjacent waters of four tidewater glaciers in Kongsfjorden, Svalbard, in early August 2016 and late July 2017. Our aim was to compare the zooplankton composition, abundance, and isotopic signatures within the plumes to those in adjacent fjord and shelf waters. Our hypothesis was that the plumes resulted in increased zooplankton mortality through osmotic shock and increased prey availability to predators. The mortality due to osmotic shock in the glacial plume was low (<5% dead organisms in samples), although slightly higher than in surrounding waters. This indicates that plumes are inefficient “death traps” for zooplankton. However, the high abundance and biomass of zooplankton within plume areas suggest that the “elevator effect” of rising glacial water supplies zooplankton to the sea surface, thereby enhancing prey availability for surface-feeding seabirds. Thus, our study provides evidence that glacial plumes are important as “climate refugia” for foraging seabirds. Stable isotope signatures showed that the glacial bay zooplankton and fish community represent a distinct isotopic niche. Additionally, zooplankton mortality associated with the plume estimated over 100-days of melt season supports a flux of 12.8 tonnes of organic carbon to benthic communities in the glacial bays. Benthic scavengers, such as Onisimus caricus and Anonyx nugax, were abundant in the glacial bay, where they feed on sinking organic matter.