Miracle-dz/UniFAR-FTUs huggingface dataset:
Does the Conservative Non-pharmacological Management of Knee Osteoarthritis in Switzerland Reflect the Clinical Guidelines? A Survey Among General Practitioners, Rheumatologists, and Orthopaedic Surgeons

Introduction: The International Guidelines recommend exercise, education and weight management (if appropriate) as the first-line conservative treatment for patients with knee osteoarthritis (OA) to enhance their self-management. The aim of this study was to investigate the current state of conservative non-pharmacological management of patients with knee OA in Switzerland and to explore the perceived barriers and facilitators to the application of the guideline recommendations. Materials and methods: Eleven semi-structured interviews with selected general practitioners (GPs), rheumatologists and orthopaedic surgeons were performed. Based on these results, an online survey was developed and sent to the members of three scientific medical societies. Questions addressed the frequency of diagnostic measures, treatment options, reasons for referral to exercise and also barriers and facilitators. Results: A total of 234 members responded. They indicated that patients normally present due to pain (n = 222, 98.2%) and functional limitations of the knee (n = 151, 66.8%). In addition to clinical assessment, X-ray (n = 214, 95.5%) and MRI (n = 70, 31.3%) were the most frequently used diagnostic measures. Treatment options usually involved patient education for diagnosis (n = 223, 98.6%) and suitable activities (n = 217, 96%), pharmacological treatment (n = 203, 89.8%) and referral to physiotherapy (n = 188, 83.2%). The participants estimated that they had referred 54% of their patients with knee OA for a specific exercise. The referral to exercise was driven by “patient expectation/high level of suffering” (n = 73, 37.1%) and their “own clinical experience” (n = 49, 24.9%). The specialists rated the most important barriers to referral to exercise as “disinterest of patient” (n = 88, 46.3%) and “physically active patient” (n = 59, 31.1%). As the most important facilitators, they rated “importance to mention exercise despite the short time of consultation” (n = 170, 89.4%) and “insufficiently physically active patient” (n = 165, 86.9%). Discussion: A substantial evidence–performance gap in the management of patients with knee OA appears to exist in Switzerland. For the systematic referral to exercise as the first-line intervention, it might be useful for medical doctors to suggest a structured exercise programme to patients with knee OA, rather than just advising general exercise.
Evaluating a Novel P300-Based Real-Time Image Ranking BCI

Brain–computer interfaces (BCIs) establish communication between a human brain and a computer or external devices by translating the electroencephalography (EEG) signal into computer commands. After stimulating a sensory organ, a positive deflection of the EEG signal between 250 and 700 ms can be measured. This signal component of the event-related potential (ERP) is called “P300. ” Numerous studies have provided evidence that the P300 amplitude and latency are linked to sensory perception, engagement, and cognition. Combining the advances in technology, classification methods, and signal processing, we developed a novel image ranking system called the Unicorn Blondy Check. In this study, the application was tested on 21 subjects using three different visual oddball paradigms. Two consisted of female faces and gray-scale images, while the third test paradigm consisted of familiar and unfamiliar faces. The images were displayed for a duration of 150 ms in a randomized order. The system was trained using 50 trials and tested with 30 trials. The EEG data were acquired using the Unicorn Hybrid Black eight-channel BCI system. These synchronized recordings were analyzed, and the achieved classification accuracies were calculated. The EEG signal was averaged over all participants and for every paradigm separately. Analysis of the EEG data revealed a significant shift in the P300 latency dependent on the paradigm and decreased amplitude for a lower target to non-target ratio. The image ranking application achieved a mean accuracy of 100 and 95.5% for ranking female faces above gray-scale images with ratios of 1:11 and 5:11, respectively. In the case of four familiar faces to 24 unfamiliar faces, 86.4% was reached. The obtained results illustrate this novel system’s functionality due to accuracies above chance levels for all subjects.
Emotional Nuance Enhances Verbatim Retention of Written Materials

Recent studies have demonstrated that details of verbal material are retained in memory. Further, converging evidence points to a memory-enhancing effect of emotion such that memory for emotional events is stronger than memory for neutral events. Building upon this work, it appears likely that verbatim sentence forms will be remembered better when tinged with emotional nuance. Most previous studies have focused on single words. The current study examines the role of emotional nuance in the verbatim retention of longer sentences in written material. In this study, participants silently read transcriptions of spontaneous narratives, half of which had been delivered within a context of emotional expression and the other half with neutral expression. Transcripts were taken from selected narratives that received the highest, most extreme ratings, neutral or emotional. Participants identified written excerpts in a yes/no recognition test. Results revealed that participants’ verbatim memory was significantly greater for excerpts from emotionally nuanced narratives than from neutral narratives. It is concluded that the narratives, pre-rated as emotional or neutral, drove this effect of emotion on verbatim retention. These findings expand a growing body of evidence for a role of emotion in memory, and lend support to episodic theories of language and the constructionist account.
Distinct Patterns of Myeloid Cell Infiltration in Patients With hrHPV-Positive and hrHPV-Negative Penile Squamous Cell Carcinoma: The Importance of Assessing Myeloid Cell Densities Within the Spatial Context of the Tumor

Comprehensive analysis of tumor infiltrating myeloid cells in the tumor microenvironment of penile squamous cell carcinoma (PSCC) is lacking. In this retrospective study, for the first time, PSCC resection specimens (N = 103) were annotated into the following compartments: intratumoral tumor (IT Tumor), intratumoral stroma (IT Stroma), peritumoral tumor (PT Tumor) and peritumoral stroma (PT Stroma) compartments. We then quantified CD14+, CD68+ and CD163+ myeloid cells within these compartments using an image analysis software and assessed their association with various clinical parameters, including high-risk human papillomavirus (hrHPV) status. In the total cohort, hrHPV status, grade of differentiation, age and tumor size were associated with myeloid cell densities. hrHPV+ tumors had higher infiltration rates of CD14+, CD68+ and CD163+ myeloid cells in the IT tumor compartment (p < 0.001, for all) compared to hrHPV− tumors. Furthermore, when examining the association between compartment-specific infiltration and differentiation grade, increased myeloid cell densities in the IT tumor compartment were associated with a more advanced histological grade (p < 0.001, for all). This association remained significant when the hrHPV− cohort (N = 60) was analyzed (CD14+ p = 0.001; CD68+ p < 0.001; CD163+ p = 0.004). Subgroup analysis in the hrHPV+ group (N = 43) showed that high infiltration rates of CD68+ and CD163+ cells in the PT tumor compartment were associated with lymph node (LN) metastasis (p = 0.031 and p = 0.026, respectively). Regarding the association between myeloid cell densities and disease-specific survival, the risk of death was found to decrease slightly as the number of myeloid cells in the IT tumor compartment increased (CD14+ p = 0.04; CD68+ p = 0.05; CD163+ p = 0.02). However, after adjusting for hrHPV, no independent association between myeloid densities and disease-specific survival were found. Altogether, these findings demonstrate the importance of assessing myeloid cell densities within the spatial context of the tumor. Further studies are needed to unravel the specific phenotype of myeloid cells residing in the different compartments, their effect on clinical parameters and the impact of hrHPV on the recruitment of myeloid cell populations in PSCC.
Advanced Modeling and Simulation of Rockfall Attenuator Barriers Via Partitioned DEM-FEM Coupling

Attenuator barriers, in contrast to conventional safety nets, tend to smoothly guide impacting rocks instead of absorbing large amounts of strain energy arresting them. It has been shown that the rock’s rotation plays an important role in the bearing capacity of these systems. Although experimental tests have to be conducted to gain a detailed insight into the behavior of both the structures and the rock itself, these tests are usually costly, time-consuming, and offer limited generalizability to other structure/environment combinations. Thus, in order to support the engineer’s design decision, reinforce test results and confidently predict barrier performance beyond experimental configurations this work describes an appropriate numerical modeling and simulation method of this coupled problem. For this purpose, the Discrete Element Method (DEM) and the Finite Element Method (FEM) are coupled in an open-source multi-physics code. In order to flexibly model rocks of any shape, sphere clusters are used which employ simple and efficient contact algorithms despite arbitrarily complicated shapes. A general summary of the FEM formulation is presented as well as detailed derivations of finite elements particularly pertinent to rockfall simulations. The presented modeling and coupling method is validated against experimental testing conducted by the company Geobrugg. Good agreement is achieved between the simulated and experimental results, demonstrating the successful practical application of the proposed method.
Triple Combination Therapy With PD-1/PD-L1, BRAF, and MEK Inhibitor for Stage III–IV Melanoma: A Systematic Review and Meta-Analysis

Triple combination of anti-PD-1/PD-L1 immunotherapy and anti-BRAF plus anti-MEK targeted therapy is a promising antitumor strategy and is increasingly being used in clinical trials. To evaluate the safety and efficacy of triple combination of PD-1/PD-L1, BRAF, and MEK inhibition in patients diagnosed with stage III-IV melanoma, we performed a systematic review and meta-analysis of randomized controlled trials (RCTs). The PubMed, EMBASE, and Cochrane Library were searched for all studies published from inception to January 2021. The progression free survival (PFS), overall survival (OS), overall response rate (ORR), and risk of adverse events (AEs) were extracted by two independent investigators and pooled hazard ratio (HR) or risk ratio (RR) with 95% CI were determined using the random-effects model for data synthesis. Overall, five randomized controlled trials encompassing 1,266 patients with stage III-IV melanoma were selected. Triple combination therapy significantly improved PFS (HR = 0.71; 95% CI = 0.59 to 0.86; P = 0.0005) and 2-year OS (RR = 1.12; 95% CI = 1.03 to 1.23; P = 0.01), but had no impact on ORR (RR = 1.09; 95% CI = 0.91 to 1.30; P = 0.37) when compared with controlled treatment group. In addition, triple combination therapy was associated with increased risks of hypothyroidism, arthralgia, myalgia, ALT increased, AST increased, asthenia, and pyrexia compared with control group. Triple combination therapy of PD-1/PD-L1, BRAF, and MEK inhibition achieved better survival benefits but had higher incidence of some adverse events over two-drug combination or monotherapy. Further randomized controlled clinical trials are needed to verify our results. Systematic Review Registration PROSPERO 2021 CRD42021235845 Available from https://www.crd. york.ac. uk/prospero/display_record. php? ID=CRD42021235845.
De novo Transcriptome Sequencing Coupled With Co-expression Analysis Reveal the Transcriptional Regulation of Key Genes Involved in the Formation of Active Ingredients in Peucedanum praeruptorum Dunn Under Bolting Period

Peucedanum praeruptorum Dunn is a perennial and one-off flowering plant of the Peucedanum genus in Umbelliferae. The cultivated P. praeruptorum Dunn usually grows nutritionally in the first year and then moves into the reproductive growth in the second year. The lignification of the roots caused by bolting leads to the quality decline of crude materials. Since most of the previous studies have dealt with coumarin biosynthesis and identification of functional genes in P. praeruptorum, the scientific connotation of the inability that the bolted P. praeruptorum cannot be used medically is still unclear. Here, we employed a transcriptome sequencing combined with coexpression analysis to unearth the regulation mechanism of key genes related to coumarin synthesis in pre- and postbolting period, and to explore the mechanisms underlying the effects of bolting on the formation and transport of coumarins between the annual and biennial plants. Six cDNA libraries were constructed, and the transcripts were sequenced and assembled by Illumina Hiseq platform. A total of 336,505 unigenes were obtained from 824,129 non-redundant spliced transcripts. Unigenes (114,488) were annotated to the NCBI nr database, 119,017 and 10,475 unigenes were aligned to Gene Ontology (GO) functional groups and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, respectively. Differential expression analysis screened out a series of upregulated and downregulated genes related to the phenylpropanoid pathway. The heatmap clustering showed that the similar expression patterns were both observed in groups C vs. D and groups C vs. F. The WGCNA-based coexpression was performed to elucidate the module and trait relationship to unearth important genes related to the bolting process. Seven pivotal modules on the KEGG functional annotations suggested these genes were mainly enriched in the process of plant–pathogen interaction, plant hormone signal transduction, MAPK signaling pathway, α-linolenic acid metabolism, circadian rhythm, and phenylpropanoid pathway. Further analysis provided clues that the key genes of the phenylpropanoid pathway, the ABC transporters, the apoptosis-related and circadian rhythm regulatory genes may play pivotal roles in regulating bolting signaling, biosynthesis, and transportation of coumarins.
CLUSTER ANALYSIS OF DEPENDENCE RELATIONSHIP OF TRACE ELEMENTS IN COAL

Four coals have been sampled and separaed into different density fractions by float-sink The content of some trace elements in each density fraction has been analyzed by ICAP Through cluster analysis for ash, sulfur and 16 trace elements, the dependence relationship of trace elements in coal is studied The results show that for alkaline-earth metals such as Be, Sr and Ba their dependence relationship are not significant, and the correlation is weaker with other elements studied Rare-earth elements such as Y, La, Ce, Sc are often symbiosis V a lithophile element is always significantly correlated with ash, and its binding ability is stronger with oxygen and weaker with sulfur As, Co and Ni, the thiophile elements, have significant correlation with pyritic sulfur The dependence relationship of trace elements in coal is related to the physicochemical property of elements, geological environment and metamorphism of coal formation
Opinion Dynamics Models with Noise

The paper analyses noise eﬀect on opinion dynamics behaviour in connection with diﬀerent noise distribution parameters. The coeﬃcient of variation, which determines the degree of noise homogeneity, was chosen as the principal characteristic of noise. In this study, a dependence was detected between the degree of noise homogeneity and the consensus-reaching time in Friedkin-Johnsen and Hegselmann-Krause opinion dynamics models.
Using Enhanced Gaussian Cross-Entropy in Imitation Learning to Digging the First Diamond in Minecraft

Although state-ofthe-art reinforcement learning (RL) systems has led to break-throughs in many difﬁcult tasks, the sample inefﬁciency of standard reinforcement learning methods still precludes their application to more extremely complex tasks. Such limitation will make many reinforcement learning systems cannot be applied to real-world problem, in which environment samples are expensive. To solve this problem, MineRL (13) provide an ideal develop environment to facilitate the research that leveraging fewer human demonstrations with more efﬁcient reinforcement learning systems. Based on the MineRL environmnet, we proposed an enhanced Gaussian cross entropy (EGCE) loss for imitation learnning problems to achieve ideal performance. In the ObtainDiamond task, our EGCE achieves about 7 . 7% improvement than a strong baseline imitation learning pipeline. The demo video is available at here .
Silica Particles Trigger the Exopolysaccharide Production of Harsh Environment Isolates of Growth-Promoting Rhizobacteria and Increase Their Ability to Enhance Wheat Biomass in Drought-Stressed Soils

In coming decades, drought is expected to expand globally owing to increased evaporation and reduced rainfall. Understanding, predicting, and controlling crop plants’ rhizosphere has the potential to manipulate its responses to environmental stress. Our plant growth-promoting rhizobacteria (PGPR) are isolated from a natural laboratory, ‘The Evolution Canyon’, Israel, (EC), from the wild progenitors of cereals, where they have been co-habituating with their hosts for long periods of time. The study revealed that commercial TM50 silica particles (SN) triggered the PGPR production of exopolysaccharides (EPS) containing D-glucuronate (D-GA). The increased EPS content increased the PGPR water-holding capacity (WHC) and osmotic pressure of the biofilm matrix, which led to enhanced plant biomass in drought-stressed growth environments. Light- and cryo-electron- microscopic studies showed that, in the presence of silica (SN) particles, bacterial morphology is changed, indicating that SNs are associated with significant reprogramming in bacteria. The findings encourage the development of large-scale methods for isolate formulation with natural silicas that ensure higher WHC and hyperosmolarity under field conditions. Osmotic pressure involvement of holobiont cohabitation is also discussed.
Eigenvalue distribution of some nonlinear models of random matrices

This paper is concerned with the asymptotic empirical eigenvalue distribution of a non linear random matrix ensemble. More precisely we consider $M= \frac{1}{m} YY^*$ with $Y=f(WX)$ where $W$ and $X$ are random rectangular matrices with i.i. d. centered entries. The function $f$ is applied pointwise and can be seen as an activation function in (random) neural networks. We compute the asymptotic empirical distribution of this ensemble in the case where $W$ and $X$ have sub-Gaussian tails and $f$ is real analytic. This extends a previous result where the case of Gaussian matrices $W$ and $X$ is considered. We also investigate the same questions in the multi-layer case, regarding neural network applications.
Factors influencing e-banking customer satisfaction and overall retention levels : perspective from a Malaysian bank Anantha

With the advancement of technology in the banking industry in recent years has led to the fulfillment of customer satisfaction with better online facilities and tracking system. Customers are able to enjoy rapid speed and service, better delivery channels and faster response rate dealing with queries and account transactions. In Malaysia, customers expect higher quality services from banks which, if fulfilled could result in significant improvement in customer satisfaction levels. This study mainly focuses on investigating to identify the major factors that influence online customers’ satisfaction with the services provided by their respective banks. This study will also assess the online transactions (internet banking) and would therefore help the banks management to improve and better service their customers and strengthen the bond between banks and their valued customers. A total of 227 customers were surveyed via online structured questionnaire for this study. This study identified core services, problem resolution, cost saved, convenience and risk and privacy concerns as the major factors affecting overall customer satisfaction in Malaysia. © 2015 Elixir All rights reserved. ARTICLE INF O Articl e h istory: Received: 22 January 2015; Received in revised form: 20 January 2015; Accepted: 12 February 2015;
Changes in Subjective versus Objective Well-Being in India

Although there is abundant literature on subjective well-being (SWB), there is virtually none for India. Growing recognition of the validity and accuracy of measures of SWB of well-being underlies the rapid growth of literature on SWB in recent decades but it has mainly focused on developed countries. Ours is, to our knowledge, the first study of SWB at the all-India level, and one of the few on developing countries, with a rigorous validation of the results. Applying robust OLS and ordered probit models to the India Human Development Survey (IHDS) panel data in 2005 and 2012, we assess SWB changes in 2005-2012, based on a self-reported measure of changes in economic well-being, as a function of household and state covariates in 2005. This is in sharp contrast with earlier studies’ focus on the levels of SWB. Another point of departure of our study and an innovative extension is to compare the covariates of SWB changes with those of objective well-being (OWB) changes, proxied by the relative growth in real per capita household consumption between 2005 and 2012. Households with an older and educated head in a larger household, located in urban areas or affluent states in 2005 tend to experience further improvement in both SWB and OWB between 2005 and 2012. On the contrary, households with a female household head, with more male members in the labour market, with regular access to mass media, without members suffering from non-communicable diseases or disability are more likely to be better off subjectively without experiencing corresponding improvement in OWB. The policy challenges raise serious concerns.
Modelling Freshwater Eutrophication with Limited Limnological Data Using Artificial Neural Networks

Artificial Neural Networks (ANNs) have wide applications in aquatic ecology and specifically in modelling water quality and biotic responses to environmental predictors. However, data scarcity is a common problem that raises the need to optimize modelling approaches to overcome data limitations. With this paper, we investigate the optimal k-fold cross validation in building an ANN using a small water-quality data set. The ANN was created to model the chlorophyll-a levels of a shallow eutrophic lake (Mikri Prespa) located in N. Greece. The typical water quality parameters serving as the ANN’s inputs are pH, dissolved oxygen, water temperature, phosphorus, nitrogen, electric conductivity, and Secchi disk depth. The available data set was small, containing only 89 data samples. For that reason, k-fold cross validation was used for training the ANN. To find the optimal k value for the k-fold cross validation, several values of k were tested (ranging from 3 to 30). Additionally, the leave-one-out (LOO) cross validation, which is an extreme case of the k-fold cross validation, was also applied. The ANN’s performance indices showed a clear trend to be improved as the k number was increased, while the best results were calculated for the LOO cross validation as expected. The computational times were calculated for each k value, where it was found the computational time is relatively low when applying the more expensive LOO cross validation; therefore, the LOO is recommended. Finally, a sensitivity analysis was examined using the ANN to investigate the interactions of the input parameters with the Chlorophyll-a, and hence examining the potential use of the ANN as a water management tool for nutrient control.