Miracle-dz/UniFAR-FTUs huggingface dataset:
Three-dimensional wavelet decomposition-based radiomics analysis for tumor characterization in patients with oropharyngeal squamous cell carcinoma

Background: We investigated the potential predictive value along with interpretability of the three-dimensional wavelet decomposition (3D-WD)-based radiomics analysis for characterization of gross-tumor-volumes (GTVs) for patients with Human Papilloma Virus (HPV) oropharyngeal squamous cell carcinoma (OPSCC). The goal was to characterize and identify the spatial frequencies and regions of primary tumor that are responsible for classifying the HPV status. Methods: One-hundred twenty-eight OPSCC patients (60-HPV+ and 68-HPV-, confirmed by immunohistochemistry-P16-Protein) were retrospectively studied. 3D-WD analysis was performed on the contrast-enhanced-CT images of patients’ primary tumor-GTVs to decompose information into three decomposition levels explained by a series of high-pass and low-pass wavelet coefficients (WCs). Log-Energy-Entropy of the WCs was calculated as radiomics features. A Least-Absolute-Shrinkage-and-Selection-Operation (Lasso) technique combined with a Generalized-Linear-Model (Lasso-GLM) was applied on the feature space to identify and rank the frequency sub-bands associated with the HPV status. The classifier was validated using a nested-cross-validation technique. Average of Area Under ROC (AUC), and Positive and Negative Predictive values (PPV and NPV) were computed to estimate the generalization-error and performance of the classifier. The significant features were used to weight tumor sub-band frequencies to reconstruct the tumor zones with highest information towards characterization of HPV. Results: Among 22 frequency-based features, two low-frequency and two high-frequency features were statistically discriminant between the two cohorts. Results (AUC/PPV/NPV=0.798/0.745/0.823) imply that tumor’s high-frequency and low-frequency components are associated with its HPV positivity and negativity, respectively. Conclusions: This study suggests that compared to the central zones of tumor, peritumoral regions contain more information for characterization of the HPV-status. Albeit subject to confirmation in a larger cohort, this pilot study presents encouraging results in support of the role of frequency-based radiomics analysis towards characterization of tumor microenvironment in patients with OPSCC. By associating this information with tumor pathology, one can potentially link radiomics to underlying biological mechanisms.
Subcritical Water Process for Reducing Sugar Production from Biomass: Optimization and Kinetics

The competitive reactions of lignocellulose hydrolysis and monosaccharide degradation in the subcritical water (SCW) hydrolysis of coconut husk were investigated to optimize the reducing sugar yield. Optimization analysis was performed by response surface methodology (RSM) and kinetics studies. Parameters of process optimization were varied at 130-170 °C for 15-45 min. The reducing sugars were measured using the Dinitro salicylic acid method. The sugar yield increased when the temperature increased from 130 °C to 170 °C. The highest reduction sugar yield of 4.946 g/L was obtained at 183.6 °C for 4.8 min and 23.4 liquid/solid ratio (LSR). Kinetics studies were carried out at temperature variations of 150, 170, and 190 °C and pressures of 60, 80, and 100 bar for 5 to 60 min. The yield of reducing sugar decreased with increasing temperature. The kinetic model 2B is the best method to explain the competitive reaction kinetics of coconut husk hydrolysis. This research is an innovation to increase the reducing sugar to make the process more commercially viable. Copyright © 2022 by Authors, Published by BCREC Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0).
Intrapore Geometry and Flow Rate Controls on the Transition of Non‐Fickian to Fickian Dispersion

Hydraulic heterogeneity leads to non‐Fickian transport characteristics, which cannot be entirely accounted for by the continuum‐scale advection‐dispersion equation. In this pore‐scale computational study, we investigate the combined effects of flow rate (i.e., Peclet number, Pe) and first‐order hydraulic heterogeneity, that is, resulting from intrapore geometry exclusively, on the transition from non‐Fickian to Fickian dispersion. A set of intrapore geometries is designed and quantified by a dimensionless pore geometry factor (β), which accounts for a broad range of pore shapes likely found in nature. Navier‐Stokes and Advection‐Diffusion equations are solved numerically to study the transport phenomenon using velocity variance, residence time distribution, and coefficients of hydrodynamic dispersion and dispersivity. We determine the length scale (i.e., the linear distance in flow direction) for each pore shape and Pe when non‐Fickian features transition to the Fickian transport regime by incrementally extending the length, that is, the linear array of pores. We show how velocity distribution and variance (σ2) depend on β, and directly control the transition to Fickian dispersion. Pores with a larger β, that is, complex pore shapes with constricted pore‐body or with “slit‐type” attributes, result in a substantial non‐Fickian characteristics. The magnitude of non‐Fickian characteristics gets amplified with an increase in Pe requiring a significantly longer length scale, that is, up to 1 m or a linear array of 500 pores to transition to the Fickian transport regime. We find the hydrodynamic dispersion coefficient (Dh) exponentially depends on the pore shape factor β, with its exponent dependent on flow rate or Pe. We determine constitutive relations to quantify how σ2, β, and Pe, contribute to the degree of non‐Fickian characteristics, the length scale needed for the transition to Fickian transport regime, asymptotic Dh, and the length‐scale dependence of longitudinal dispersivity.
Role of steroid on management of limb swelling and local pain in haematotoxic snake bite

ABSTRACT Introduction: Local Pain and swelling in the biting area of haematotoxic snake bite victims are very common symptoms. This study was conducted to retrospectively observe the effect of oral Tab Prednisolone on a short-term basis as an add-on therapy of haematotoxic snake bite management in respect of Local Pain and swelling recovery. Materials and Methods: This retrospective descriptive study was conducted in a tertiary care hospital in West Bengal among 36 haematotoxic snake bite victims, admitted from February 2020 to January 2021. After collection of the data from hospital records and screened by inclusion and exclusion criteria, 36 participants were included in two groups based on the treatment regimen. Group A (n: 24) received only conventional treatment and Group B (n: 12) received oral Tab Prednisolone on a short-term basis as an add-on therapy of conventional treatment. Swelling was measured as a distance from the site of the bite with measuring tape in centimeters and pain was measured by a numerical rating pain scale (NRS) between 0 and 10. Ethical permission has been waived from the Institutional Ethical Review Committee. Result: A total of 36 patients (32 male and 4 female) were included in the study. Age (Mean ± SD) of the snake victim persons in Group A and Group B were 35.79 ± 8.34 years and 31.33 ± 6.47 years, respectively. The local swelling length and pain score reduced significantly among group B patients on day 6 in comparison to day 2. However, in Group A, the pain score and local swelling increased significantly on day 6 in comparison to day 2. Conclusion: A short course of systemic steroids as an adjuvant with anti-venom serum (ASV) for the management of local pain and edema in case of haematotoxic snake bite may be beneficial if there is no contraindication.
Uncertainty modelling in mass comparisons.

To evaluate uncertainty in mass measurements with accuracy and in accordance with recent international documents, a general model is developed, which takes account of the various contributing quantities in a multivariate context. On this basis, the variance-covariance matrix of the in-vacuo mass differences is constructed in its general form and tailored for application to some of the most commonly adopted weighing methods. The usual assumption of equal-variance, uncorrelated observations is shown to be inappropriate for mass comparisons.
A DIGITAL EDUCATIONAL GAME FOR PRACTICING OER

Making education available to everyone is about opening new doors to the future world where people are living with their full abilities and potentials. This vision was acknowledged by UNESCO and it was one of the main motives for introducing Open Educational Resources (OER) in 2002. Over the last two decades, OER have made a positive impact on spreading quality educational information. However, the lack of experience in using and practicing OER is one of the common reasons why people have difficulties utilizing OER without violating copyright laws. To overcome this problem, a workshop concept was designed in order to qualify educators for OER. As part of the workshops, a digital educational game has been developed to elevate the participants’ motivation and engagement. The game covers all basic aspects of the OER cycle (creating, editing, using, and distributing OER) and is designed to be played within the practical sessions. By implementing this game and utilizing the concept of Game-based Learning (GBL), we wanted to provide an interactive learning environment to practice OER and motivate learners to explore the OER world. In this paper, we present the concept of the game and demonstrate its technical foundation as well as its functionalities.
Adaptive leader-follower formation control of non-holonomic mobile robots using active vision

This study is concerned with the leader-follower formation control of non-holonomic mobile robots without communication. A pan-controlled camera is the sole sensor used by the follower to observe the leader. A new vision-based formation system without range states is proposed, which eliminates the need of inter-robot range estimation. An adaptive formation controller and an adaptive camera controller are designed in the presence of unknown leader's velocities and vision-related parameters. A parameter projection algorithm is integrated into the controllers to bound the control inputs. The camera controller ensures the stable observation of the leader's features. Thus the camera constantly provides visual measurements for the formation controller which guarantees the formation maintenance. Simulation and experimental results verify the effectiveness of the proposed active vision-based formation control approach.
Optimization of CO2 Laser Parameters for Hole Micro Drilling of PMMA: An Experimental and Theoretical Study

Motivated by a desire to improve hole quality during drilling Polymethyl methacrylate (PMMA) samples using a continuous CO2 laser. This research presents a theoretical and experimental investigation to optimize input parameters of laser drilling such as laser power and exposure time for different thicknesses 1-3 (mm). Hole quality characteristics such as depth, inlet diameter, and heat affected zone (HAZ) were considered process results and examined with a microscope. Design Expert software has been used to get a detailed understanding of a laser drilling process owing to the confluence of multiple factors that impacts the results. depending on the Box Behnken Design (BBD) of tests software; 17 experiments were applied to explore the effect of laser factors on the micro-hole drilling process. Statistical analysis technique (ANOVA) was used to study the influence of laser drilling process factors including power, exposure time of different thicknesses on HAZ, depth, and entrance diameter. Quadratic regression models were employed to model the processing of many hole variables. Experiments were optimized using the defined goal model as a function to get the optimal hole. The data received were confirmed using verification tests, and a considerable increase in hole quality was realized. The proposed technique is perfect for reducing the HAZ and entrance hole diameter for the ideal depth hole. The laser parameters were changed in different combinations of 2-6 (W) power and 0.1- 0.3 (s) exposure duration, on the various thickness. The obtained values indicated that raising the drilling parameters increases the depth, entrance diameter, and HAZ. The sample thickness has a great impact on hole characteristics; increasing the sample thickness reduces the inlet diameter, and heat-affected zone (HAZ); increasing the thickness leads to an increase in hole depth. The results showed that the highest depth of 1mm thick was 0.99(mm) with 437(µm) diameter and 85(µm) HAZ. 1.9(mm) depth with 435(µm) diameter and 32(µm) HAZ was obtained at 4.99(W) and 0.1(s) on 2(mm) thickness. while as in 3(mm) thick, depth is equal to 2.8(mm), 472(µm) diameter, and 20(µm) HAZ was attained. COMSOL Multiphysics 5.6 software was used to apply virtual experiments and obtain the ideal conditions from the parameters' combination that improves the quality of the hole, which is the main goal of this research. Which is in good agreement with the test results. The findings and procedure of this research have not been presented elsewhere.
Aiding Animals: Does Foreign Aid Reduce Wildlife Crime?

The illegal wildlife trade has come to the forefront of global politics, driven by concerns about biodiversity loss, illicit markets, and animal-borne infectious diseases. Yet, poaching remains common in many countries. The persistence of illegal hunting is attributable to (among other factors) poverty and poor labor market opportunities, which leave individuals in some communities with few viable alternatives to wildlife crime. Foreign aid that alleviates poverty and unemployment may, therefore, lead to a reduction in illegal hunting. However, cross-national research on aid and economic development offers mixed findings, suggesting a conditional effect. Against this backdrop, I theorize that aid reduces the economic pressures that contribute to poaching, but only in countries with representative political institutions. I test a corresponding hypothesis using data on elephant poaching in African and Asian countries. My findings show that aid is accompanied by a reduction in elephant poaching in democracies, but not in authoritarian countries.
How Does Perceived Organizational Support Reduce the Effect of Working Environmental Risk on Occupational Strain? A Study of Chinese Geological Investigators

Background: Sensitivity to working environmental risks is essential to ensure the safety of geological investigators, but persistent perceived risks may lead to occupational strain, with negative effects on physical and mental health. This study aimed to find ways to reduce the negative consequences of working environmental risk perception without losing situational awareness. Methods: A questionnaire survey was conducted with 268 participants from geological survey organizations, measuring their perception of working environmental risk, occupational strain, perceived organizational support, and other stressors. Results: (1) The perception of working environmental risk and occupational strain of geological investigators was significantly higher than that of administrative staff, managers, and scientific researchers. (2) Working environmental risk is an important predictor of occupational strain in geological investigators even after controlling for other stressors. (3) Different dimensions of perceived organizational support play different roles in stress management; socio-emotional support negatively predicts occupational strain, and instrumental support moderates the relationship between working environmental risk perception and occupational strain. Conclusions: Our findings identify working environmental risk as one of the most prominent stressors for geological investigators. Socio-emotional support directly reduces occupational strain, while instrumental support buffers the effect of risk perception on occupational strain.
The Impact of Quality of Big Data Marketing Analytics (BDMA) on the Market and Financial Performance

Impact of quality of big data marketing analytics (BDMA) was analyzed, with special attention to the BDMA dimensions of technology and information quality, and the level of deployment on perceived market and financial performance. The sample was collected with Canadian and U.S. marketing respondents with experience in big data (BD) deployment (N=236). The model analysis was done with PLS-SEM. The study highlights how technology and information quality are related to the market and financial performance with high predictive validity and strength. Also, the level of deployment had a significant impact on both the technology and information quality in BDMA. The study provides an understanding of how the level of deployment impacts BDMA technology and information quality dimensions; and how they individually contribute to the enhancement of a firm's market and financial performance from the perspective of marketing personnel with experience in deployment of BDMA. It is also evident that the more advanced the firm is in the deployment of BD, the higher the technology and information quality.
The use of a new optimization criterion for discrete-time feedback controller design

We introduce a class of linear discrete-time systems called "super stable". For the SISO case this means that the absolute value of the constant term of the characteristic polynomial is greater than the sum of absolute values of all other coefficients, while super stable MIMO systems have a state matrix with l/sub 1/ norm less than one. Such systems have many special features. Within the framework of these systems we can, using linear programming, design fixed-order controllers. We also address robustness issues, including robust performance for transfer functions with coprime factor uncertainty bounded in l/sub 1/ norm.
Real-World Outcomes Associated With Letermovir Use for Cytomegalovirus Primary Prophylaxis in Allogeneic Hematopoietic Cell Transplant Recipients: A Systematic Review and Meta-analysis of Observational Studies

Abstract Background A systematic review and meta-analysis of real-world observational studies was conducted to summarize the impact of letermovir cytomegalovirus (CMV) primary prophylaxis (PP) among adult allogeneic hematopoietic cell transplant (allo-HCT) recipients. Methods Systematic searches in Medline/PubMed, Embase, and conferences (from database inception to October 2021) were conducted to identify studies for inclusion. Random-effects models were used to derive pooled estimates on the relative effectiveness of letermovir PP compared to controls. Results Forty-eight unique studies (N = 7104 patients) were included, most of which were comparative, single-center, and conducted in the United States. Letermovir PP was associated with statistically significant reduction in odds of CMV reactivation (pooled odds ratio [pOR], 0.13 and 0.24; P < .05), clinically significant CMV infection (pOR, 0.09 and 0.19; P < .05), and CMV disease (pOR, 0.31 and 0.35; P < .05) by day +100 and day +200 after allo-HCT, respectively. Letermovir PP was associated with significantly lower odds of all-cause (pOR, 0.73; P < .01) and nonrelapse mortality (pOR, 0.65; P = .01) beyond day 200 after allo-HCT. Conclusions Letermovir for CMV PP was effective in reducing the risk of CMV-related complications overall and mortality beyond day 200 among adult allo-HCT recipients.
An image processing and machine learning solution to automate Egyptian cotton lint grading

Egyptian cotton is one of the most important commodities for the Egyptian economy and is renowned globally for its quality, which is largely assessed and graded by manual inspection. This grading has several drawbacks, including significant labor requirements, low inspection efficiency, and influence from inspection conditions such as light and human subjectivity. This work proposes a low-cost solution to replace manual inspection with classification models to grade Egyptian cotton lint using images captured by a charge-coupled device camera. While this method has been evaluated for classifying US and Chinese upland cotton staples, it has not been tested on Egyptian cotton, which has unique characteristics and grading requirements. Furthermore, the methodology to develop these classification models has been expanded to include image processing techniques that remove the influence of trash on color measurements and extract features that capture the intra-sample variance of the cotton samples. Three different supervised machine learning algorithms were evaluated: artificial neural networks; random forest; and support vector machines. The highest accuracy models (82.13–90.21%) used a random forest algorithm. The models’ accuracy was limited by the human error associated with labeling the cotton samples used to develop the classification models. Unsupervised machine learning methods, including k-means clustering, hierarchical clustering, and Gaussian mixture models, were used to indicate where labeling errors occurred.
Machine learning methods applied for the prediction of biological activities of triple reuptake inhibitors

Abstract Major depressive disorder (MDD) is characterized by a series of disabling symptoms like anhedonia, depressed mood, lack of motivation for daily tasks and self-extermination thoughts. The monoamine deficiency hypothesis states that depression is mainly caused by a deficiency of monoamine at the synaptic cleft. Thus, major efforts have been made to develop drugs that inhibit serotonin (SERT), norepinephrine (NET) and dopamine (DAT) transporters and increase the availability of these monoamines. Current gold standard treatment of MDD uses drugs that target one or more monoamine transporters. Triple reuptake inhibitors (TRIs) can target SERT, NET, and DAT simultaneously, and are believed to have the potential to be early onset antidepressants. Quantitative structure-activity relationship models were developed using machine learning algorithms in order to predict biological activities of a series of triple reuptake inhibitor compounds that showed in vitro inhibitory activity against multiple targets. The results, using mostly interpretable descriptors, showed that the internal and external predictive ability of the models are adequate, particularly of the DAT and NET by Random Forest and Support Vector Machine models. The current work shows that models developed from relatively simple, chemically interpretable descriptors can predict the activity of TRIs with similar structure in the applicability domain using ML methods. Communicated by Ramaswamy H. Sarma
A Position Statement on Mpox as a Sexually Transmitted Disease

Abstract The global outbreak of mpox virus constituted an international public health emergency. Reports have highlighted (1) a temporal association between sexual activity and mpox, (2) an association between specific sexual practices and location of lesion development, (3) a high frequency of sexual practices conferring risk for other sexually transmitted infections among cases of mpox, (4) that mpox virus can be isolated from sexual fluids, (4) that isolated virus is infectious, and (5) a high frequency of anogenital lesions prior to disease dissemination suggesting direct inoculation during sexual activities. Finally, a growing body of evidence suggests that sexual transmission is the predominant mode of transmission for mpox virus. We therefore conclude that mpox is a sexually transmitted disease. Labeling it as such will help focus public health interventions, such as vaccinations, testing, and treatment, as well as facilitate focused awareness and education programs toward behavioral modifications to reduce exposures.