Miracle-dz/UniFAR-FTUs huggingface dataset:
Learning Better Intent Representations for Financial Open Intent Classification

With the recent surge of NLP technologies in the financial domain, banks and other financial entities have adopted virtual agents (VA) to assist customers. A challenging problem for VAs in this domain is determining a user’s reason or intent for contacting the VA, especially when the intent was unseen or open during the VA’s training. One method for handling open intents is adaptive decision boundary (ADB) post-processing, which learns tight decision boundaries from intent representations to separate known and open intents. We propose incorporating two methods for supervised pre-training of intent representations: prefix tuning and fine-tuning just the last layer of a large language model (LLM). With this proposal, our accuracy is 1.63% - 2.07% higher than the prior state-of-the-art ADB method for open intent classification on the banking77 benchmark amongst others. Notably, we only supplement the original ADB model with 0.1% additional trainable parameters. Ablation studies also determine that our method yields better results than full fine-tuning the entire model. We hypothesize that our findings could stimulate a new optimal method of downstream tuning that combines parameter efficient tuning modules with fine-tuning a subset of the base model’s layers.
Long-Tailed Food Classification

Food classification serves as the basic step of image-based dietary assessment to predict the types of foods in each input image. However, foods in real-world scenarios are typically long-tail distributed, where a small number of food types are consumed more frequently than others, which causes a severe class imbalance issue and hinders the overall performance. In addition, none of the existing long-tailed classification methods focus on food data, which can be more challenging due to the inter-class similarity and intra-class diversity between food images. In this work, two new benchmark datasets for long-tailed food classification are introduced, including Food101-LT and VFN-LT, where the number of samples in VFN-LT exhibits real-world long-tailed food distribution. Then, a novel two-phase framework is proposed to address the problem of class imbalance by (1) undersampling the head classes to remove redundant samples along with maintaining the learned information through knowledge distillation and (2) oversampling the tail classes by performing visually aware data augmentation. By comparing our method with existing state-of-the-art long-tailed classification methods, we show the effectiveness of the proposed framework, which obtains the best performance on both Food101-LT and VFN-LT datasets. The results demonstrate the potential to apply the proposed method to related real-life applications.
Residual Learning of Neural Text Generation with n-gram Language Model

N -gram language models (LM) have been largely superseded by neural LMs as the latter exhibits better performance. However, we ﬁnd that n -gram models can achieve satisfactory performance on a large proportion of testing cases, indicating they have already captured abundant knowledge of the language with relatively low computational cost. With this observation, we propose to learn a neural LM that ﬁts the residual between an n -gram LM and the real-data distribution. The combination of n -gram and neural LMs not only allows the neural part to focus on the deeper understanding of language but also provides a ﬂexible way to customize an LM by switching the underlying n -gram model without changing the neural model. Experimental results on three typical language tasks (i.e., language modeling, machine translation, and summarization) demonstrate that our approach attains additional performance gains over popular stan-dalone neural models consistently. We also show that our approach allows for effective domain adaptation by simply switching to a domain-speciﬁc n -gram model, without any extra training. Our code is released at https: //github.com/ghrua/NgramRes .
Multi Points Updated and Distance Filtered Kriging Surrogate Model： Application in EOSS Optimization

We put forward a multi points updated and distance filtered Kriging surrogate model. When building Kriging models, two update approaches are used to select infilling points: optimal points and maximized expected improvement. We use Improved general pattern search (IGPS) algorithm to get these points. In IGPS, search step is substituted by GA and SQP and poll step is retained. To decrease simulation times, we adopt a distance filter to eliminate potentially replicated samples. A satellite or- bit parameter optimization problem is formulated, which is solved by the proposed method and STK/Analyzer re- spectively. The results showed that Kriging models, which use multi update points and distance filter, yield global approximations that are more accurate than Analyzer.
Exploring Language-independent Digital Speech Biomarkers of Hypokinetic Dysarthria

Motor speech disorders in patients with Parkinson's disease (PD), collectively referred to as hypokinetic dysarthria, are the early markers of the disease. Acoustic speech features are, therefore, suitable digital biomarkers for the diagnosis and monitoring of this pathological phenomenon. At the same time, it is clear that language plays an essential role in using these features to classify speech successfully into healthy and dysarthric one. This paper focuses on the multilingual analysis of the currently used and newly proposed acoustic speech features and their use in the supportive diagnosis of PD. The goal is to explore digital speech biomarkers of PD, focusing on their language independence and high discrimination power using statistical analysis and machine learning techniques. Thirty-three acoustic features of Czech, American, Israeli, Columbian and Italian PD patients and healthy controls were analyzed using correlation and statistical tests, descriptive statistics, and the XGBoost classifier with posterior explanation by features importances and Shapley values. The features quantifying the prominence of the second formant, monopitch, and the lower number of pauses detected during text reading show the best results, both by statistical analysis and machine learning. Classification accuracies range from 67% to 85%, depending on the language. The paper introduces the concept of language robustness as a quality in which a feature behaves the same, independently of the language. By using this new concept along with other metrics, it proposes several digital speech biomarkers that have the potential to be language-independent with high discrimination power.
Étude comparative de patients hospitalisés pour une infection SARS-CoV-2 au cours de deux vagues consécutives en Tunisie

Résumé Introduction Le nouveau coronavirus (SARS-CoV-2) a déclenché une pandémie mondiale avec des conséquences sanitaires qui n’étaient pas similaires lors des vagues successives qui ont touché plusieurs pays. Le but de notre étude était de comparer les caractéristiques socio-démographiques, cliniques et évolutives des patients atteints de la COVID-19 hospitalisés au cours des 2e et 3e vagues survenues en Tunisie. Patients et méthodes Étude prospective observationnelle incluant 1 527 patients atteints de la COVID-19 et hospitalisés à l'Hôpital militaire de Tunis, s’étalant sur 11 mois, répartie en deux périodes : de juillet 2020 jusqu'en décembre 2020 appelée la deuxième vague (V2) et de janvier 2021 jusqu'en mai 2021 appelée la troisième vague (V3). Résultats 636 patients ont été hospitalisés au cours de V2 contre 891 au cours de V3. L’âge moyen était de 63,5 ± 15,3 ans au cours de V2 contre 65,8 ± 17,8 ans au cours de V3 (P = non significatif [NS]). Le sexe-ratio (H/F) était de 1,59 pour V2 et de 1,42 pour V3 (P = NS). La forme clinique sévère représentait 49% des cas pendant V2 contre 34,8% pendant V3 (P < 10-3). La forme critique représentait 18,6% des cas au cours de V2 contre 16,8% au cours de V3 (P = NS). Le taux de létalité était de 24,5% au cours de V2 et de 20,7% au cours de V3 (P = NS). L’âge médian des patients décédés était de 70,2 ans [42-88 ans] au cours de V2 et de 70,4 ans [22-96 ans] au cours de V3. Le sexe-ratio (H/F) des patients décédés était de 3,21 pour V2 et de 1,5 pour V3 (P = 0,001). Le taux de létalité était plus élevé dans le service de réanimation (65,4% pour V2 versus 69,7% pour V3; P = NS). Les causes de décès étaient dominées par le SDRA (syndrome de détresse respiratoire aiguë) pour les deux périodes (55,1% pour V2 versus 70,8% pour V3; P = 0,002), suivi de l’état de choc septique (12,8% pour V2 versus 10,8% pour V3; P = NS) et de la défaillance multiviscérale (9,6% pour V2 versus 7,0% pour V3; P = NS). Conclusion Nous avons observé une diminution des formes cliniques sévères et critiques au cours de V3, ainsi qu'une baisse du taux de létalité par rapport à V2 grâce à l'amélioration de la prise en charge ainsi qu’à la vaccination. En revanche, le pourcentage de SDRA était significativement plus élevé au cours de V3 probablement en rapport avec le début de circulation dans notre pays de la souche Delta à l'origine de tableaux cliniques plus sévères.
The Role of Microorganisms and Carbon-to-Nitrogen Ratios for Microbial Protein Production from Bioethanol

The global protein demand is rapidly increasing at rates that cannot be sustained, with projections showing 78% increased global protein needs by 2050 (361 compared to 202 million tonprotein/year in 2017). In the absence of dedicated mitigation strategies, the environmental effects of our current food production system (relying on agriculture) are expected to surpass the planetary boundaries—the safe operating space for humanity—by 2050. ABSTRACT With industrial agriculture increasingly challenging our ecological limits, alternative food production routes such as microbial protein (MP) production are receiving renewed interest. Among the multiple substrates so far evaluated for MP production, renewable bioethanol (EtOH) is still underexplored. Therefore, the present study investigated the cultivation of five microorganisms (2 bacteria, 3 yeasts) under carbon (C), nitrogen (N), and dual C-N-limiting conditions (molar C/N ratios of 5, 60, and 20, respectively) to evaluate the production (specific growth rate, protein and biomass yield, production cost) as well as the nutritional characteristics (protein and carbohydrate content, amino acid [AA] profile) of MP production from bioethanol. Under C-limiting conditions, all the selected microorganisms showed a favorable AA profile for human nutrition (average AA score of 1.5 or higher), with a negative correlation between protein content and growth rate. Maximal biomass yields were achieved under conditions where no extracellular acetate was produced. Cyberlindnera saturnus and Wickerhamomyces anomalus displayed remarkably high biomass yields (0.40 to 0.82 g cell dry weight [CDW]/g EtOHconsumed), which was reflected in the lowest estimated biomass production costs when cultivated with a C/N ratio of 20. Finally, when the production cost was evaluated on a protein basis, Corynebacterium glutamicum grown under C-limiting conditions showed the most promising economic outlook. IMPORTANCE The global protein demand is rapidly increasing at rates that cannot be sustained, with projections showing 78% increased global protein needs by 2050 (361 compared to 202 million tonprotein/year in 2017). In the absence of dedicated mitigation strategies, the environmental effects of our current food production system (relying on agriculture) are expected to surpass the planetary boundaries—the safe operating space for humanity—by 2050. Here, we illustrate the potential of bioethanol—renewable ethanol produced from side streams—as a main resource for the production of microbial protein, a radically different food production strategy in comparison to traditional agriculture, with the potential to be more sustainable. This study unravels the kinetic, productive, and nutritional potential for microbial protein production from bioethanol using the bacteria Methylorubrum extorquens and Corynebacterium glutamicum and the yeasts Wickerhamomyces anomalus, Cyberlindnera saturnus, and Metschnikowia pulcherrima, setting the scene for microbial protein production from renewable ethanol.
Autophagy, cell death, and cytokines in K. pneumoniae infection: therapeutic perspectives

ABSTRACT Klebsiella pneumoniae is a notorious nosocomial pathogen causing a wide range of infections. The increasing trend of antimicrobial resistance obtained by the species immensely highly challenges the clinical treatment, representing a large threat to the global health care network. In particular, the recent convergence of multidrug resistance and hypervirulence in K. pneumoniae further worsens clinical outcomes, resulting in high mortality. Developments of new therapeutics become urgent, and immunotherapy based on antagonizing the anti-immune strategies of pathogens is a promising strategy, which requires the understanding of immune evasion mechanism in the context of the host–pathogen interactions. However, the underlying mechanisms employed by K. pneumoniae to counteract host immune responses, especially autophagy and cell death, have not been systematically reviewed and discussed yet. This review aims to summarize the tremendous progress that has been made to illuminate the landscape of cell signalling triggered by K. pneumoniae infection, especially in aspects of manipulating autophagy, cell death, and cytokine production.
The effect of cardiac properties on arterial pulse waves: An in‐silico study

This study investigated the effects of cardiac properties variability on arterial pulse wave morphology using blood flow modelling and pulse wave analysis. A lumped‐parameter model of the left part of the heart was coupled to a one‐dimensional model of the arterial network and validated using reference pulse waveforms in turn verified by comparison with in vivo measurements. A sensitivity analysis was performed to assess the effects of variations in cardiac parameters on central and peripheral pulse waveforms. Results showed that left ventricle contractility, stroke volume, cardiac cycle duration, and heart valves impairment are determinants of central waveforms morphology, pulse pressure and its amplification. Contractility of the left atrium has negligible effects on arterial pulse waves. Results also suggested that it might be possible to infer left ventricular dysfunction by analysing the timing of the dicrotic notch and cardiac function by analysing PPG signals. This study has identified cardiac properties that may be extracted from in vivo central and peripheral pulse waves to assess cardiac function.
The nearby strongly reddened open cluster Stock2 . A new study based on accurate proper motions and 2MASS photometry

The open cluster Stock 2 is situated in the Orion spiral arm and is affected by a strong and patchy interstellar extinction. These characteristics make its investigation rather demanding and a difficult task. We decided to tackle this cluster by means of an integrate use of astrometric and photometric observations. Here we present new results based on accurate proper motions, that we used to identify kinematically the cluster members over an area of 70’x70’. Also, an extinction local map was derived by means of 2MASS photometry and used to produce the unreddered CMD of the cluster. Finally, new, although preliminary, determinations of the cluster distance and age are presented and discussed.
The impact of Parkinson’s disease on results of primary total knee arthroplasty

Parkinson’s disease (PD) is a common neurodegenerative disorder. When patients with PD undergo total knee arthroplasty (TKA) for knee osteoarthritis, poorer knee function and poorer quality of life are obtained than in matched cohorts (MCs). However, the degree of patient satisfaction is usually high. The mean length of stay is 6.5% longer in patients with PD than in MCs. Compared with MCs, patients with PD undergoing TKA have a 44% higher risk of complications. In patients with PD, the overall complication rate is 26.3% compared with 10.5% in MCs; the periprosthetic joint infection rate is 6.5% in patients with PD vs 1.7% in MCs; and the periprosthetic fracture rate is 2.1% in patients with PD vs 1.7% in MCs. The 90-day readmission rate is 16.29% in patients with PD vs 12.66% in MCs. More flexion contractures occur in patients with PD. The rate of medical complications is 4.21% in patients with PD vs 1.24% in MCs, and the rate of implant-related complications is 5.09% in patients with PD vs 3.15% in MCs. At 5.3 years’ mean follow-up, the need for revision surgery is 23.6%. The 10-year implant survival, taking revision of any of the components as an endpoint, is 89.7% in patients with PD vs 98.3% in MCs.
Evidence-based updates to the 2021 Surviving Sepsis Campaign guidelines

Abstract: Sepsis identification and treatment has changed significantly over the last few decades. Despite this, sepsis is still associated with significant morbidity and mortality. This first of a two-part series reviews the history of modern sepsis and presents new research in pathophysiology, treatment, and postsepsis care. Sepsis identification and treatment has changed significantly over the last few decades. Despite this, sepsis is still associated with significant morbidity and mortality. This first of a two-part series reviews the history of modern sepsis and presents new research in pathophysiology, treatment, and postsepsis care.
Basal bodies bend in response to ciliary forces

Motile cilia beat with an asymmetric waveform consisting of a power stroke that generates a propulsive force and a recovery stroke that returns the cilium back to the start. Cilia are anchored to the cell cortex by basal bodies (BBs) that are directly coupled to the ciliary doublet microtubules (MTs). We find that, consistent with ciliary forces imposing on BBs, bending patterns in BB triplet MTs are responsive to ciliary beating. BB bending varies as environmental conditions change the ciliary waveform. Bending occurs where striated fibers (SFs) attach to BBs and mutants with short SFs that fail to connect to adjacent BBs exhibit abnormal BB bending, supporting a model in which SFs couple ciliary forces between BBs. Finally, loss of the BB stability protein Poc1, which helps interconnect BB triplet MTs, prevents the normal distributed BB and ciliary bending patterns. Collectively, BBs experience ciliary forces and manage mechanical coupling of these forces to their surrounding cellular architecture for normal ciliary beating.
Transient receptor potential canonical 6 knockdown ameliorated diabetic kidney disease by inhibiting nuclear factor of activated T cells 2 expression in glomerular mesangial cells

Abstract Purpose Glomerular mesangial cell (GMC) dysfunction plays a vital role in the pathogenesis of diabetic kidney disease (DKD). Transient receptor potential canonical 6 (TRPC6) has been demonstrated to be involved in the development of DKD. However, the underlying mechanism remains unclear. The present study investigated the role of TRPC6 in GMC dysfunction and the related mechanism. Methods Diabetic rats and cultured GMCs were used in the experiment. The diabetic rat model was created by intraperitoneal injection of streptozotocin. Protein and mRNA levels were assessed by Western blotting and quantitative RT–PCR, respectively. Histological changes in the kidneys were observed by immunochemistry and hematoxylin and eosin. TRPC6 knockdown was achieved by adenovirus-mediated TRPC6 shRNA delivery in vivo and TRPC6 siRNA transfection in vitro. Results TRPC6 expression was increased in diabetic rat kidneys. Knockdown of TRPC6 attenuated diabetes-induced kidney functional deterioration. In addition, the increases in extracellular matrix components, including collagen IV, collagen I, and fibronectin production, as well as NFAT2 expression were also suppressed. In cultured GMCs, high glucose (25 mM, HG) treatment increased the expression of TRPC6. Knockdown of TRPC6 alleviated HG-induced increases in collagen IV, fibronectin, and NFAT2 expression. Knockdown of NFAT2 also inhibited the upregulation of proteins, including collagen IV and fibronectin, in HG-treated GMCs. Conclusion These results demonstrate that inhibition of TRPC6/NFAT2 signaling attenuates GMC dysfunction and the development of DKD and suggest that pharmacological targeting of TRPC6/NFAT2 in GMCs may provide beneficial effects for DKD.
Development and validation of seven phosphatidylethanol-homologues in dried blood spots including preliminary results after excessive use of an ethanol-based hand sanitizer

Abstract Phosphatidylethanol (PEth) has become a widespread marker offering an up to four weeks retrospective window to detect alcohol use. Due to the COVID 19 pandemic, ethanol-based hand sanitizers are frequently used. The aim of this study was to develop and validate a method for determination of up to seven different homologues of PEth from dried blood spots (DBS) after use of an ethanol-based hand sanitizer. Objectives of its preliminary application were to prove whether a threshold of 20 ng/mL for PEth 16:0/18:1 is reached and whether other homologues are formed as well as if positive findings of urinary ethyl glucuronide (UEtG) can be observed with respect to assess monitoring of abstinence control programs. Ten volunteers (8 occasional, 2 regular drinkers) were recruited to excessively use an ethanol-based hand sanitizer on 5 successive days. Dried blood spots and urine samples were collected daily. PEth and UEtG were determined by LC-MS/MS. In total, two volunteers with initial PEth 16:0/18:1-concentrations of 19.3 and 14.6 ng/mL exceeded the threshold of 20 ng/mL six times. Regular drinkers had starting PEth 16:0/18:1-concentrations of 242 and 354 ng/mL, showing a decline of PEth-concentrations in six out of the seven homologues over five days. In teetotalers, formation of PEth species could not be observed. Thus, not satisfying requirements in an alcohol monitoring program with initial PEth-negative blood cannot be explained by a frequent use of ethanol-based hand sanitizer only. In cases of regular alcohol consumption, PEth-homologues are not likely to be further influenced. However, results indicated that individuals with a PEth-concentration close to 20 ng/mL are at risk of exceeding the threshold by using ethanol-based hand sanitizer.
How workplace‐based assessments guide learning in postgraduate education: A scoping review

Competency‐based medical education (CBME) led to the widespread adoption of workplace‐based assessment (WBA) with the promise of achieving assessment for learning. Despite this, studies have illustrated tensions between the summative and formative role of WBA which undermine learning goals. Models of workplace‐based learning (WBL) provide insight, however, these models excluded WBA. This scoping review synthesizes the primary literature addressing the role of WBA to guide learning in postgraduate medical education, with the goal of identifying gaps to address in future studies.