Testicular mapping-guided sperm retrieval upfront microTESE in non-obstructive azoospermia: a comparison of sperm retrieval, pregnancy and live-birth rates.

Background: Sperm extraction by Microscopic Testicular Sperm Extraction (microTESE) has become the standard of care for sperm retrieval (SR) in men with non-obstructive azoospermia (NOA) but is costly and has a 40-50% chance of failure. Fine needle aspiration mapping (FNAM) can be performed prior to microTESE as a predictor of success to reduce the likelihood of failure to retrieve sperm but there is limited evidence that directly compares these methods. The objective of this study was to compare success rate of SR, pregnancy, and live birth rates in men who underwent upfront microTESE versus FNAM.

Emergency management of orbital compartment syndrome: Lateral canthotomy and cantholysis case series.

Background: Orbital compartment syndrome (OCS) is considered a time critical condition that requires urgent surgical decompression to preserve vision. This study aims to evaluate the current clinical criteria for performing a lateral canthotomy and cantholysis (LCC) in the emergency management of suspected traumatic OCS.

Methods: A retrospective audit of patients with suspected traumatic OCS presenting to an adult major trauma centre between January 1, 2017, and August 1, 2022, was performed.

Comparison of protection against mpox following mRNA or modified vaccinia Ankara vaccination in nonhuman primates.

In 2022, mpox virus (MPXV) spread worldwide, causing 99,581 mpox cases in 121 countries. Modified vaccinia Ankara (MVA) vaccine use reduced disease in at-risk populations but failed to deliver complete protection. Lag in manufacturing and distribution of MVA resulted in additional MPXV spread, with 12,000 reported cases in 2023 and an additional outbreak in Central Africa of clade I virus.

The Influence of and Fibers on the Thermal Properties and Flammability of Polylactide Composites.

This study focuses on examining the influence of bast fibers on the flammability and thermal properties of the polylactide matrix (PLA). For this purpose, and fibers were subjected to two types of modifications: mercerization in NaOH solution (M1 route) and encapsulation in an organic PLA solution (M2 route). In a further step, PLA composites containing 5, 10, and 15 wt% of unmodified and chemically treated fibers were obtained.

Research on the Development of a Way to Modify Asphalt Mixtures with PET Recyclates.

Due to the growing need to recycle plastics, new possibilities for their reuse are intensively sought. In the Asian market, waste polymers are increasingly used to modify road bitumen. This solution is beneficial in many aspects, especially in economic and ecological terms.

Novel gramine-based bioconjugates obtained by click chemistry as cytoprotective compounds and potent antibacterial and antifungal agents.

A series of indole-1,4-disubstituted-1,2,3-triazole conjugates were synthesised by click chemistry. The haemolytic properties and cytoprotective activity of all the newly synthesised indole-triazole conjugates were tested . In addition, molecular docking was performed for the selected conjugates to determine their antibacterial and antifungal properties.

Effects of Small Deviations in Fiber Orientation on Compressive Characteristics of Plain Concrete Cylinders Confined with FRP Laminates.

The effectiveness of concrete confinement by fiber-reinforced polymer (FRP) materials is highly influenced by the orientation of fibers in the FRP laminates. In general, acceptable deviation limit from the intended direction is given as 5° in most design guidelines, without solid bases and reasoning. In this paper, a numerical study using finite element modeling was conducted to assess the effects of small deviations in fiber orientation from the hoop direction on compressive behavior of concrete cylinders confined with FRP.

Assessment of the Actual Toxicity of Engine Exhaust Gas Emissions from Euro 3 and Euro 6 Compliant Vehicles with the BAT-CELL Method Using In Vitro Tests.

Legal restrictions on vehicle engine exhaust gas emission control do not always go hand in hand with an actual reduction in the emissions of toxins into the atmosphere. Moreover, the methods currently used to measure exhaust gas emissions do not give unambiguous results on the impact of the tested gases on living organisms. The method used to assess the actual toxicity of gases, BAT-CELL Bio-Ambient-Tests using in vitro tests, takes into account synergistic interactions of individual components of a mixture of gases without the need to know its qualitative and quantitative composition and allows for determination of the actual toxicity of the gas composition.

Electrospinning of Poly (Acrylamide), Poly (Acrylic Acid) and Poly (Vinyl Alcohol) Nanofibers: Characterization and Optimization Study on the Effect of Different Parameters on Mean Diameter Using Taguchi Design of Experiment Method.

In this study, nanofibers of poly (acrylic acid) (PAAc), polyacrylamide (PAAm) and poly (vinyl alcohol) (PVOH) were prepared using the electrospinning technique. Based on the Taguchi DOE (design of experiment) method, the effects of electrospinning parameters, i.e.

Preparation and Characterization of Novel Microgels Containing Nano-SiO and Copolymeric Hydrogel Based on Poly (Acrylamide) and Poly (Acrylic Acid): Morphological, Structural and Swelling Studies.

In this paper, novel microgels containing nano-SiO were prepared by in situ copolymerization using nano-SiO particles as a reinforcing agent, nanosilica functional monomer (silane-modified nano-SiO) as a structure and morphology director, acrylamide (AAm) as a monomer, acrylic acid (AAc) as a comonomer, potassium persulfate (KPS) as a polymerization initiator, and N,N'-methylene bis (acrylamide) (MBA) as a crosslinker. In addition, a conventional copolymeric hydrogel based on poly (acrylamide/acrylic acid) was synthesized by solution polymerization. The microgel samples, hydrogel and nanoparticles were characterized by transmission electron microscopy (TEM), field emission scanning electron microscopy (FESEM), Fourier transform infrared (FTIR) spectroscopy, thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC).

Consideration of Critical Parameters for Improving the Efficiency of Concrete Structures Reinforced with FRP.

Fibre-reinforced polymer materials (FRP) are increasingly used to reinforce structural elements. Due to this, it is possible to increase the load-bearing capacity of polymer, wooden, concrete, and metal structures. In this article, the authors collected all the crucial aspects that influence the behaviour of concrete elements reinforced with FRP.

Predicting the Mechanical Properties of RCA-Based Concrete Using Supervised Machine Learning Algorithms.

Environment-friendly concrete is gaining popularity these days because it consumes less energy and causes less damage to the environment. Rapid increases in the population and demand for construction throughout the world lead to a significant deterioration or reduction in natural resources. Meanwhile, construction waste continues to grow at a high rate as older buildings are destroyed and demolished.

Assessment of Soft Computing Techniques for the Prediction of Compressive Strength of Bacterial Concrete.

In this investigation, the potential of M5P, Random Tree (RT), Reduced Error Pruning Tree (REP Tree), Random Forest (RF), and Support Vector Regression (SVR) techniques have been evaluated and compared with the multiple linear regression-based model (MLR) to be used for prediction of the compressive strength of bacterial concrete. For this purpose, 128 experimental observations have been collected. The total data set has been divided into two segments such as training (87 observations) and testing (41 observations).

Novel Synthesis, Characterization and Amoxicillin Release Study of pH-Sensitive Nanosilica/Poly(acrylic acid) Macroporous Hydrogel with High Swelling.

The effect of SiO nanoparticles on the formation of PAA (poly acrylic acid) gel structure was investigated with seeded emulsion polymerization method used to prepare SiO/PAA nanoparticles. The morphologies of the nanocomposite nanoparticles were studied by transmission electron microscopy (TEM). Fourier-transform infrared (FTIR) spectroscopy results indicated that the PAA was chemically bonded to the surface of the SiO nanoparticles.

Development of Prediction Model to Predict the Compressive Strength of Eco-Friendly Concrete Using Multivariate Polynomial Regression Combined with Stepwise Method.

Concrete is the most widely used building material, but it is also a recognized pollutant, causing significant issues for sustainability in terms of resource depletion, energy use, and greenhouse gas emissions. As a result, efforts should be concentrated on reducing concrete's environmental consequences in order to increase its long-term viability. In order to design environmentally friendly concrete mixtures, this research intended to create a prediction model for the compressive strength of those mixtures.

Simulation of Depth of Wear of Eco-Friendly Concrete Using Machine Learning Based Computational Approaches.

To avoid time-consuming, costly, and laborious experimental tests that require skilled personnel, an effort has been made to formulate the depth of wear of fly-ash concrete using a comparative study of machine learning techniques, namely random forest regression (RFR) and gene expression programming (GEP). A widespread database comprising 216 experimental records was constructed from available research. The database includes depth of wear as a response parameter and nine different explanatory variables, i.

Effect of Carbon Black and Hybrid Steel-Polypropylene Fiber on the Mechanical and Self-Sensing Characteristics of Concrete Considering Different Coarse Aggregates' Sizes.

The effect of combining filler (carbon black) and fibrous materials (steel fiber and polypropylene fiber) with various sizes of coarse particles on the post-cracking behavior of conductive concrete was investigated in this study. Steel fibers (SF) and carbon black (CB) were added as monophasic, diphasic, and triphasic materials in the concrete to enhance the conductive properties of reinforced concrete. Polypropylene fiber (PP) was also added to steel fiber and carbon to improve the post-cracking behavior of concrete beams.

Computation of High-Performance Concrete Compressive Strength Using Standalone and Ensembled Machine Learning Techniques.

The current trend in modern research revolves around novel techniques that can predict the characteristics of materials without consuming time, effort, and experimental costs. The adaptation of machine learning techniques to compute the various properties of materials is gaining more attention. This study aims to use both standalone and ensemble machine learning techniques to forecast the 28-day compressive strength of high-performance concrete.

Prediction of Geopolymer Concrete Compressive Strength Using Novel Machine Learning Algorithms.

The innovation of geopolymer concrete (GPC) plays a vital role not only in reducing the environmental threat but also as an exceptional material for sustainable development. The application of supervised machine learning (ML) algorithms to forecast the mechanical properties of concrete also has a significant role in developing the innovative environment in the field of civil engineering. This study was based on the use of the artificial neural network (ANN), boosting, and AdaBoost ML approaches, based on the python coding to predict the compressive strength (CS) of high calcium fly-ash-based GPC.

Application of Advanced Machine Learning Approaches to Predict the Compressive Strength of Concrete Containing Supplementary Cementitious Materials.

The casting and testing specimens for determining the mechanical properties of concrete is a time-consuming activity. This study employed supervised machine learning techniques, bagging, AdaBoost, gene expression programming, and decision tree to estimate the compressive strength of concrete containing supplementary cementitious materials (fly ash and blast furnace slag). The performance of the models was compared and assessed using the coefficient of determination (R), mean absolute error, mean square error, and root mean square error.

A Comparative Study for the Prediction of the Compressive Strength of Self-Compacting Concrete Modified with Fly Ash.

Artificial intelligence and machine learning are employed in creating functions for the prediction of self-compacting concrete (SCC) strength based on input variables proportion as cement replacement. SCC incorporating waste material has been used in learning approaches. Artificial neural network (ANN) support vector machine (SVM) and gene expression programming (GEP) consisting of 300 datasets have been utilized in the model to foresee the mechanical property of SCC.

Analyzing the Compressive Strength of Ceramic Waste-Based Concrete Using Experiment and Artificial Neural Network (ANN) Approach.

In a fast-growing population of the world and regarding meeting consumer's requirements, solid waste landfills will continue receiving a substantial amount of waste. The utilization of solid waste materials in concrete has gained the attention of the researchers. Ceramic waste powder (CWP) is considered to be one of the most harmful wastes for the environment, which may cause water, soil, and air pollution.

Evaluation of the impact of marijuana use on semen quality: a prospective analysis.

Aims: To assess if marijuana consumption - prevalent among men of reproductive age and becoming widespread due to decriminalization - is associated with changes in semen parameters. Marijuana's active metabolite, tetrahydrocannabinol, can alter signaling pathways within spermatozoa, affecting spermatogenesis and fertility.

Methods: We prospectively evaluated semen analyses (SA) from men presenting for infertility evaluation at one institution from July 2017 to April 2018.

Comparative Study of Supervised Machine Learning Algorithms for Predicting the Compressive Strength of Concrete at High Temperature.

High temperature severely affects the nature of the ingredients used to produce concrete, which in turn reduces the strength properties of the concrete. It is a difficult and time-consuming task to achieve the desired compressive strength of concrete. However, the application of supervised machine learning (ML) approaches makes it possible to initially predict the targeted result with high accuracy.

The Influence of CFRP Sheets on the Load-Bearing Capacity of the Glued Laminated Timber Beams under Bending Test.

Composite materials are increasingly used to strengthen existing structures or new load-bearing elements, also made of timber. In this paper, the effect of the number of layers of Carbon Fiber Reinforced Polymer (CFRP) on the load-bearing capacity and stiffness of Glued Laminated Timber beams was determined. Experimental research was performed on 32 elements-a series of eight unreinforced beams, and three series of eight reinforced beams: with one, three and five layers of laminate each.