Miracle-dz/UniFAR-FTUs huggingface dataset:
Validation of a Machine Learning Model to Predict Immunotherapy Response in Head and Neck Squamous Cell Carcinoma

Simple Summary Recurrent and/or metastatic head and neck squamous-cell carcinoma (R/M HNSCC) is a clinically challenging disease with a poor prognosis. Despite advances in survival through the use of immune-checkpoint blockade, only a minority of patients experience benefit from such treatments, and it is difficult to identify the patients most likely to benefit. Machine learning approaches integrating clinical and genomic data can predict response to immune-checkpoint blockade across all cancers; however, the performance of this model in HNSCC has not been examined. Here, we validate this previously described immune-checkpoint blockade response prediction model in R/M HNSCC patients. This model was able to predict response as well as overall survival following immune-checkpoint blockade in patients with R/M HNSCC. Further investigation will be needed to further delineate the importance of HNSCC-specific features. Abstract Head and neck squamous-cell carcinoma (HNSCC) is a disease with a generally poor prognosis; half of treated patients eventually develop recurrent and/or metastatic (R/M) disease. Patients with R/M HNSCC generally have incurable disease with a median survival of 10 to 15 months. Although immune-checkpoint blockade (ICB) has improved outcomes in patients with R/M HNSCC, identifying patients who are likely to benefit from ICB remains a challenge. Biomarkers in current clinical use include tumor mutational burden and immunohistochemistry for programmed death-ligand 1, both of which have only modest predictive power. Machine learning (ML) has the potential to aid in clinical decision-making as an approach to estimate a tumor’s likelihood of response or a patient’s likelihood of experiencing clinical benefit from therapies such as ICB. Previously, we described a random forest ML model that had value in predicting ICB response using 11 or 16 clinical, laboratory, and genomic features in a pan-cancer development cohort. However, its applicability to certain cancer types, such as HNSCC, has been unknown, due to a lack of cancer-type-specific validation. Here, we present the first validation of a random forest ML tool to predict the likelihood of ICB response in patients with R/M HNSCC. The tool had adequate predictive power for tumor response (area under the receiver operating characteristic curve = 0.65) and was able to stratify patients by overall (HR = 0.53 [95% CI 0.29–0.99], p = 0.045) and progression-free (HR = 0.49 [95% CI 0.27–0.87], p = 0.016) survival. The overall accuracy was 0.72. Our study validates an ML predictor in HNSCC, demonstrating promising performance in a novel cohort of patients. Further studies are needed to validate the generalizability of this algorithm in larger patient samples from additional multi-institutional contexts.
Comparative Analysis of Effectiveness of Audio-Visual Distraction Using Virtual Reality Glasses along with WAND Injection System vs Conventional Injection Technique in Reducing Dental Anxiety in Children Using Salivary Cortisol as an Anxiety Marker: An invivo Study

Objectives: To compare and assess the levels of dental anxiety in children before and after administration of local anesthesia using audiovisual distraction, WAND injection system, and Audiovisual distraction along with WAND injection system compared to the conventional injection technique using salivary cortisol as a marker of dental anxiety and SEM and VAS as Anxiety assessment tools. Methods: The study was conducted in the Department of Pediatric and Preventive Dentistry, Krishnadevaraya College of Dental Sciences & Hospital, Bengaluru, with a sample of 48 children aged 6-12 years who required local infiltration anesthesia for various dental procedures. They were randomly divided into 4 main groups viz Conventional LA with Audiovisual distraction, Conventional LA without Audiovisual distraction, WAND LA with Audiovisual Distraction, and WAND LA without distraction, they were then subdivided into 4 sub-groups according to their
ANNAGNPS: ACCOUNTING FOR SNOWPACK, SNOWMELT, AND SOIL FREEZE-THAW

The watershed model, AnnAGNPS (Annualized AGricultural Non-Point Source Pollution model) has been enhanced by incorporating winter climate algorithms that account for frozen soil conditions. The model includes snowpack accumulation and melt, and the freeze-thaw process in the soil. Three major improvements can be expected for watersheds with significant winter climates. First, the model will better account for the lag in runoff from precipitation held for months in snowpack. Second, the model will more accurately account for the movement of water through the soil layers and any resulting runoff. Third, the model will better account for the increase in sheet and rill erosion due to runoff over soil layers that have experienced the freeze-thaw process. These model improvements synthesize the science of the SHAW model (Simultaneous Heat and Water) by Gerald Flerchinger, Agricultural Research Service, Boise Idaho. SHAW, however, is a research model, while AnnAGNPS is a watershed model used by engineers and other practitioners for practical applications. In adapting SHAW, several modifications in computational procedures were made. For example, while the AnnAGNPS heat flux algorithm retains a simultaneous matrix solution of the temperature profile in soil and snow layers, the default timesteps and solution tolerances are larger than in SHAW. In addition, the first release of winter-enhanced AnnAGNPS will not include a full simultaneous matrix solution of soil moisture in thermal layers, as is done in SHAW. AnnAGNPS may adopt this in the future, but presently computes soil moisture in a more simplified manner. Also, SHAW includes a thermal layer for surface residue. This highly desired model component will be incorporated into AnnAGNPS in a future release. The AnnAGNPS winter enhancements improve modeling capability for many more geographic locations and will result in better sediment yield and pollutant loading estimates for water quality improvement in natural resources planning.
Joint Probability Description of Design Rainfalls

In the currently applied rainfall-based flood estimation methods, design storms for pre-defined durations are represented by probabilistic design rainfall intensities and fixed temporal patterns. This does not adequately reflect the great degree of variability of real storm events and, in catchments with strongly non-linear runoff response, may lead to significantly biased flood estimates. The paper proposes a new definition for storm events of random duration. It demonstrates that a joint probability description of design rainfall using these new storm events is quite feasible, and explores their potential for practical design flood estimation applications.
Information, Communication and Environment : Marine Navigation and Safety of Sea Transportation

The present paper describes an experiment where a VTS uses the functionality of “route suggestion” to visually support communication between navigators and VTS Operators. The idea of “route suggestion”, a crucial part of current developments within e-navigation, was first introduced with the EfficienSea project and has since been matured within the MONALISA and ACCSEAS projects. Within the ACCSEAS project the functionality has been augmented through the notion of “intended routes”, where vessels transmit sections of their planned routes using ECDIS in order for navigators to better understand the intentions of other, nearby, vessels. Also, “route suggestions” has been developed for use by shore stations, such as VTS, to transmit route segments to individual vessels within its area of responsibility. As part of the ACCSEAS project, the latter was tested in a simulator consisting of two full mission bridges and two VTSs, each of the two working in pairs, bridge-VTS. Five different scenarios were used, all set in the entrance of the river Humber, UK. In total, nine Pilots/Masters (Unlimited licence) and two VTS Operators participated in the experiment which ran over four days and was divided into two different simulations. ECDIS and VTS system were represented by the shipboard as well as the shore-based E-navigation Prototype Display system, as developed by the Danish Maritime Authority within the MONALISA and ACCSEAS projects. Data was collected using questionnaires, observation and video protocols. The observation protocol and the video protocol were coded and micro coded using MaxQDA and the questionnaires were used for comparison between the different participants following the analysis of protocol data in MaxQDA. Results indicate that there were no differences in acceptance of the tested “route suggestion” functionality between participants of different age, nor previous experiences as navigators/VTS Operators. Further, the results strongly indicate that the acceptance of the “route suggestion” functionality was due to the VTS Operators bridging the introduction of the new functionality by voice communication. Thus, the “route suggestion” functionality served as a graphical means of supporting voice communication between navigator and VTS Operator.
Forecasting International Stock Market Trends: XGBoost, LSTM, LSTM-XGBoost, and Backtesting XGBoost Models

Forecasting time series is crucial for financial research and decision-making in business. The nonlinearity of stock market prices profoundly impacts global economic and financial sectors. This study focuses on modeling and forecasting the daily prices of key stock indices - MASI, CAC 40, DAX, FTSE 250, NASDAQ, and HKEX, representing the Moroccan, French, German, British, US, and Hong Kong markets, respectively. We compare the performance of machine learning models, including Long Short-Term Memory (LSTM), eXtreme Gradient Boosting (XGBoost), and the hybrid LSTM-XGBoost, and utilize the skforecast library for backtesting. Results show that the hybrid LSTM-XGBoost model, optimized using Grid Search (GS), outperforms other models, achieving high accuracy in forecasting daily prices. This contribution offers financial analysts and investors valuable insights, facilitating informed decision-making through precise forecasts of international stock prices.
Perceptions of Self-Efficacy and Perceived Benefits in Adolescents About Covid-19 Vaccine in the Working Area of Telaga Dewa Health Center, Bengkulu City

SARS-COV-2 is the virus that causes Corona Virus Disease-19, an infectious disease. As of April 17, 2022, Bengkulu, one of the corona virus-infected provinces, has 29,099 confirmed cases and 167 fatalities. The new goal of 52% of 2,215 youth has not been met in terms of youth vaccination rates. The study's objective was to examine how adolescents in Bengkulu City's Telaga Dewa Health Center worked with the Covid-19 vaccine. In-depth interviews with theory of the health belief model and focus group discussion approaches are two of the qualitative methods used in this study to get information. The results are given as descriptive data that has been prepared verbally based on the outcomes of in-depth interviews with informants. Teenagers (15–17 years old) who were divided into 5 groups 5 who had received vaccinations and 5 who had not as well as 2 support groups consisting of parents of teenagers and Covid-19 vaccine professionals served as the study's informants. In order to implement the health belief model, this study collected data from a group of adolescents who had received vaccinations and those who had not. It was discovered that the adolescents had a positive perception of their vulnerability, were aware of the seriousness of the Covid-19 virus which can be fatal and the advantages of the Covid-19 vaccine. However, based on the experiences of those closest to them, the adolescents were still unclear about the vaccine's side effects. Adolescent immunization rates should be increased, according to recommendations.
Influence of Aperture of Radiating Strip Structure on Electrodynamic Characteristics of Patch Antenna

The paper presents the results of numerical modeling of the electrodynamic characteristics of a Vivaldi type patch antenna based on a circular disk resonator. The modeling was carried out using the semi-open resonator model by the finite element method (FEM) implemented in the HFFS package. The antenna was fed using a coplanar line segment. The antenna elements were placed over a grounded plane. The influence of design parameters and the function determining the curvature of the exponentially expanding slot discontinuity on the frequency, energy and polarization characteristics was investigated. It was established that with a certain selection of variable parameters, such an antenna can be matched with external circuits in the range from 7.03 GHz to 20 GHz with a level of VSWR values not exceeding 1.92. In the amplitude-frequency characteristic, fairly wide frequency bands with almost perfect matching are observed. The choice of the type of excitation element in the form of a section of the coplanar line made it possible to exclude additional elements inherent in Vivaldi antennas, namely, a section of the auxiliary strip line and a balancing resonator. This kind of antenna allows to form radiation patterns of various shapes from single-sided to cosecant quadrate. At the same time, in some intervals of observation angles, the formed fields turn out to be elliptically polarized with an ellipticity coefficient close to unity. The combination of the obtained results makes it possible to predict the use of this kind of antennas for operation with broadband signals.
Exploration of Resnet Variants in High Spatial Resolution Domain Adaptation

Abstract. When mapping land cover from airborne to spaceborne data, a problem arises, where the difference in sensors between the two shows a large spatial resolution inconsistency and spectral differences. Consequently, the same object may exhibit completely different features. This problem causes models trained from annotated airborne to be ineffective when applied to spaceborne. Cross-Sensor Land-COVER (LoveCS) shows good results in overcoming this problem. LoveCS leverages small-scale aerial image annotations to promote land cover mapping on large-scale spacecraft. LoveCS uses ResNet50 as its encoder. In recent years, many studies have tried to develop other variants of ResNet, such as ResNeXt, ResNeSt, Res2Net, and Res2NeXt. This variation of ResNet turned out to give better results in a variety of tasks compared to ResNet. Therefore, in this study we modified the LoveCS encoder by replacing ResNet50 with ResNet variants such as ResNeXt, ResNeSt, Res2Net, and Res2NeXt in an effort to improve LoveCS accuracy. We also offer LoveCS schemes with better accuracy based on the best encoders. Our evaluation shows that Res2Net50 as an encoder is able to improve LoveCS performance where the average F1 increases by 1.38%, OA by 1.96%, and Kappa by 2.75% from the baseline method.
Modeling of kilometers radio wave propagation on a high latitudes in summer and winter time

The report is devoted to the foundation of the method of calculation of the service zone of the MF radio beacon for transmission of differential corrections of the global navigation satellite system (GNSS) over high-latitude manysectional impedance paths in summer and winter time. Methods of calculation of the Earth’s wave field over inhomogeneous radio paths including over layered “ice-sea” structure are considered. On a base of the analysis of propagation conditions of radio waves, a new method of calculation of the service zone of the radio lines in the Arctic basin was submitted. Numerical algorithms for various models of the propagation of radio waves were developed and tested. The method consists in using the proposed set of algorithms, maps of geoelectric sections (GES) of underlying layered medium, digital relief maps, vegetation and ice cover for the calculations of Earth’s wave fields.
The Influence of Hiatuses on Sediment Accumulation Rates

Hiatuses pervade the stratigraphic record at all scales from grain boundaries to inter-regional unconformities. Every attempt to measure a rate of accumulation must average together sediment increments and surfaces of hiatus. As the time span of measurement lengthens, longer hiatuses tend to be incorporated into the estimated rate. Consequently, short term rates are systematically faster than longer term rates. As would be expected for a fractal time series, the empirical relationship between accumulation rate and the time span of measurement is a negative power law. Just as a measured length for a coastline is meaningless without a statement of the map scale, a measured rate of sediment accumulation requires a statement of the time scale of measurement. Fractal scaling laws offer a means to estimate and interpret the changes in average accumulation rate from one time scale to another. The steepness of the negative power law that relates rate to time span increases with the incompleteness of the stratigraphic record. For steady accumulation and complete sections the slope would be zero. For the most incomplete and unsteady accumulation, the slope approaches minus one. A purely random accumulation process produces a power law with a slope of minus one half; less steep negative slopes indicate some degree of persistence or positive correlation between successive sediment increments; steeper negative slopes prove a negative correlation. Regular periodic fluctuations in accumulation are one form of negative correlation; they produce steep negative slopes at time scales close to the period of the fluctuations. In shallow marine carbonate environments the negative power laws steepen markedly at time spans of tens of thousands to hundreds of thousands of years; the time scale suggests that the steepening records the preponderance of hiatuses that have been generated by Milankovitch-scale changes of sea-level. A plot of the age and level of sediment increments preserved in a stratigraphic section has a staircase-like shape, in which the treads represent surfaces of hiatus. Sequence boundaries of known age fix the coordinates of points on these treads. Rocks dated by radiometric techniques fix the coordinates of points on the risers. Horizons across which the fauna, isotopic composition or magnetic polarity are found to change may correspond to points on either the treads or the risers. The staircase plot forms the lower bound of the true accumulation history which would be determined by continuous monitoring of the elevation of the sediment surface during accumulation. Thus, the relationship of accumulation rate to time span also depends to some extent upon the method used to date the sediment.
Image semantic segmentation with finer edges and complete parts from bounding box annotations

Abstract. Image semantic segmentation understands and parses the image scene from the pixel-level. We work on the weakly supervised image semantic segmentation method on bounding box annotations. Inspired by Roberts edge detection operator, we develop an edge gradient module, which includes the max-pooling layer and average-pooling layer to extract edge gradient features. We combine the pyramid pooling (PP) module extracting global features with the atrous spatial PP module building the relationships between nodes to form long-range context dependency module. It can strengthen the ties between various parts of the object, just like a simplified fully connected conditional random field. To obtain more accurate feedback from bounding box annotations, we design a random label transformation algorithm. Finally, we demonstrate the validity of our module on PASCAL VOC 2012 and MS-COCO datasets, and our whole model has achieved a better performance than other mainstream methods.
Controls on Arctic glacier-fed river water temperature

ABSTRACT The impact of climate change on Arctic rivers is expected to be severe. There is therefore a need for greater understanding of Arctic river temperature processes. This study quantifies the spatio-temporal variability of water temperatures in the Kårsa River, Sweden. Water temperature was monitored over two summers within the main proglacial channel and within braids fed by different sources. Longitudinal and lateral temperature patterns were assessed in relation to prevailing hydro-meteorology. Temperature metrics in the main channel increased with distance downstream but were moderated by a large lake, while temperatures in the braids were dependent upon channel source. The high temperature standard deviation and inter-site differences within the braids highlight the importance of braided channels for creating thermal habitat heterogeneity. Temperatures were dependent on hydro-meteorological conditions, with sensitivity to air temperature maximized during cooler, rainy conditions. These results shed new light on Arctic river temperature patterns and their controlling processes.
Improving User Experience: Designing an Intuitive and Visually Appealing Interface for University First Contact and Ombudsman Services for the Centro Universitario del Sur

In an unprecedented effort to comprehensively address the issues of gender violence, harassment, and bullying, the University of Guadalajara has implemented a support structure that involves the University Rights Ombudsman (DDU, Defensoria de los Derechos Universitarios, acronym in Spanish), the Unit for Equality (UI, Unidad de Igualdad, acronym in Spanish), and the First Contact offices (PC, Primeros Contactos, acronym in Spanish). Furthermore, The University of Guadalajara has established the Protocol for the Prevention, Attention, Sanction, and Eradication of gender violence (PPASE, Protocolo para la Prevención, Atención, Sansión y Erradicación de la Violencia de Género, acronym in Spanish) [1]. The University of Guadalajara has a network of university campuses throughout the state of Jalisco in Mexico. The Centro Universitario del Sur is one of these campuses, commonly referred to as CUSur. Despite these significant advancements in the implementation of the PPASE, the university community at CUSur generally faces challenges in understanding the processes, situations, and characteristics of these entities and regulations, placing victims or potential victims in a vulnerable situation. It is essential to expedite the information and attention processes for potential victims, and in this regard, technology can play a pivotal role. We are developing a technological intervention strategy to facilitate access for the university community, especially for victims who need to utilize the resources offered by the University of Guadalajara. To achieve this goal, we research user experience and identify the current usability of the webpage, focusing on understanding specific needs and challenges. The goal is to design an intuitive and appealing user interface that provides clear and accessible information about the available processes, services, and resources. Leveraging best practices in Human-Computer Interaction (HCI) is expected to enhance the visualization of the attention processes and foster trust in the entities responsible for providing support.