Browse Articles

Correlation analysis between multifidus muscle atrophy and the severity of degenerative scoliosis retrospective, cross-sectional study

Spatial distribution characteristics and tourism response of intangible cultural heritage in coastal areas of China

Fabrication and characterization of carbon and glass fiber reinforced thermoplastic composites by fused filament fabrication

Manipulation of the photonic spin hall shift using the four levels atomic system

The comorbidities of diarrhea and acute respiratory tract infection and risk factors among under-five children in 45 low- and middle-income countries

The association between fronto-insular interaction and executive function during childhood and adolescence in a resting state fMRI study

Research on UAV aerial imagery detection algorithm for Mining-Induced surface cracks based on improved YOLOv10

Immunological role and prognostic value of ITGA3 and ITGA5 in oral squamous cell carcinoma

A study of the radon seasonality with temporal dummy variables

Exploring the shared genetic basis between autism spectrum disorder and gastrointestinal disorders: a bioinformatic study

Impact of cryopreservation agents on sperm quality, DNA fragmentation, and apoptotic markers in fertile and infertile males

Abstract Semen cryopreservation is a crucial technique for preserving male fertility, playing a vital role in assisted reproductive procedures by storing frozen semen samples for artificial insemination (AI) and intra-cytoplasmic sperm injection (ICSI) to enhance reproductive success rates. This study aims to identify the most effective cryopreservation methods and assess their impact on semen quality, particularly sperm DNA fragmentation. A total of 30 semen samples were categorized into fertile and infertile groups. DNA fragmentation analysis was conducted using the Sperm Chromatin Structure Assay (SCSA). Each sample was divided into three portions and frozen using different cryoprotectants: (egg-yolk + glycerol), (sucrose + glycerol), and (glycerol alone). After one month of storage, the samples were analyzed to determine the most effective medium. The findings revealed a decline in sperm motility post-freezing compared to fresh samples, along with a slight increase in morphological abnormalities. Additionally, there was a rise in sperm DNA fragmentation and an increase in apoptotic marker (Caspase-3) levels after the freezing process. The study concluded that cryopreservation and thawing caused some degree of sperm cell damage, with infertile samples being more adversely affected than fertile ones.

The interactions of non-functionalized polystyrene nanoparticles with human albumin and erythrocyte proteins: implications and potential consequences

Research on the impact of algorithmic trading on market volatility

Abstract The rapid growing of algorithmic trading (AT) has been playing an increasingly important role in shaping financial market in recent years. Although many scholars have studied the impact of AT on market volatility, the evidence they provided is inconsistent. Whether and how AT influence on market volatility is still not clear, especially for emerging markets. In this paper, using level 2 quotations from Chinese market, we answered the question. By introducing multiple mediator model, we found that AT can significantly reduce market volatility. In addition to the influence of AT itself, the sentiment effect accounts for approximate 1/4 of the influence, and a very small portion, about 4%, of the influence can be explained by herd effect. Besides, it also illustrated that the influences of AT are more sensitive in main board, rather than in GEM board. Nevertheless, the sentiment effect has been playing plays more important role in the influence of AT in GEM board. These findings provide new insights into previous inconsistent evidence regarding the influence of AT on market volatility. They also have important implications for investment strategies and market regulations.

Leveraging assistive technology for visually impaired people through optimal deep transfer learning based object detection model

Improved faster R-CNN for steel surface defect detection in industrial quality control

Hygroscopic properties modeling and thermodynamic analysis of a seamless popping capsule

Abstract This study investigated the thermal stability of seamless “popping” capsules at different storage temperatures to address the challenges of adhesion and texture changes affecting shelf life. Storage experiments at different temperatures identified optimal conditions for maintaining product integrity. Moisture adsorption behavior was analyzed using isothermal adsorption curves at 25 °C, 32 °C, and 37 °C, along with sorption kinetics at 68% relative humidity (RH). Capsules lost commercial viability at 37 °C and higher, and the moisture sorption isotherms followed Type II patterns. The Smith model best fit data at 25 °C and 37 °C (R2 > 0.98), while the GAB model was more suitable at 32 °C (R2 > 0.98). The storage humidity should not exceed 61% RH. The sorption process reached a state of saturation within two hours and followed first-order kinetics (R2 > 0.95). Thermodynamic analysis showed that sorption was enthalpy-driven and non-spontaneous, with an isokinetic temperature of 324.76 K and Gibbs free energy of 45.57 J/(mol·K). Attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) identified moisture-binding sites, and Scanning Electron Microscopy (SEM) revealed structural changes due to moisture exposure. These findings improve understanding of moisture sensitivity in seamless capsules and guide optimal storage conditions to preserve product quality.

Effect of alkali activator and granulated blast furnace slag on the properties of lithium slag-based high-strength lightweight aggregates

Effect of crop type shift on soil C:N:P stoichiometry in a typical Yellow River irrigated district

Abstract The Hetao irrigation area is one of the largest irrigation areas in the Yellow River Basin and is a typical salinized agricultural area. Crop type shifts can affect soil stoichiometric ratio characteristics, indicating soil nitrogen and phosphorus availability and the soil degradation process. However, few studies have been conducted in this area. In this study, soil samples were collected at 45 sites under sunflower fields (SF) and other land (OL), and the SF were mostly shifted by the OL. The results revealed that the soil pH and salinity clearly increased while the OL shifted to the SF. Moreover, soil organic matter (SOM), total nitrogen (TN), and total phosphorus (TP) also decreased significantly. These findings indicate that the soil degradation process accelerated during crop type conversion. Moreover, with the transition from OL to SF, there was little difference in the C: N ratio, whereas the C:P and N:P ratios decreased significantly. The soil P mineralization rates increased, and the N limits improved during the crop type shift. In addition, the soil C:N, C:P, and N:P ratios decreased overall with increasing soil depth. This research provides new insight for the management of crop types and the improvement of soil properties in the saline‒alkali soil of the Yellow River irrigation area.

Developing a reliable predictive model for the biodegradability index in industrial complex effluent

Abstract The interaction between chemical oxygen demand (COD) and biological oxygen demand (BOD5) in wastewater from Tehran’s Paytakht and Nasirabad Industrial Parks is investigated in this work. Monitoring platforms of industrial parks were the base frame of monthly collection data for laboratory measurements (for BOD5 and COD) and in-situ measurements (for DO, EC and Temperature-T°C) with a frequency of 4-hour samples/day. Backward elimination regression analysis was employed as an integrated procedure to find out effective model removing ineffective independent variables. Multivariate Regression analysis showed a relatively strong linear relationship between COD and BOD, with independent variables with R²=0.64 and R²=0.59, respectively. A prediction model for BOD based on COD was found by analyzing important effluent quality variables using simple linear regression and a strong linear association (BOD = 0.433COD + 222) with R² = 0.94, MSE = 38,829, RMSE = 197.05 was obtained. In all of these regression analyses, model accuracy was assessed by conducting statistical tests on the residuals. To verify and improve the reliability and practicability of model, it is applied of industrial parks’ wastewater records of countries around the world such as Egypt, France, India, Pakistan and Malaysia. The extracted model applied on some of the mentioned countries’ records and the results of BOD prediction was matched by observations in 95% of reliability domain. Variation of BOD-COD ratio was least affected by pH and temperature; the results underline the requirement of localized validation resulting from industry-specific differences and promote cost-effective, quick wastewater evaluation, hence lowering reliance on laboratory-based BOD5 testing. It defiantly provides the opportunity of analytical and applied researches in south countries toward sustainable industrial wastewater management.

First night effect alters occipital brain connectivity in horses

Abstract The First Night Effect is a phenomenon whereby sleep duration and quality are compromised in unfamiliar environments or situations. Horses are often transported to new locations, such as sporting events. We wanted to know if the First Night Effect is also detectable in horses in two different populations. To investigate this, we compared five horses from a professional sports horse barn that are regularly used in competitions, with six horses from a breeding barn, that are less frequently transferred to unfamiliar places. Despite the significant differences observed in electroencephalography (EEG) patterns and behavior between the two horse populations, we were able to identify EEG changes indicative of the First Night Effect. These changes were most apparent in the delta band at the occipital position of the brain, indicating fluctuations in sleep-wake dynamics and consciousness. Furthermore, in this study, EEG data outperformed behavioral data in the detection of the First Night Effect, indicating the usefulness of EEG measurements for monitoring welfare or even assessing stress and pain.