Miracle-dz/UniFAR-FTUs huggingface dataset:
Development and Effect Verification of Beef Cattle Carcass Grading Camera Equipment System

This paper first discusses the development status of beef cattle carcass grading and photographic equipment at home and abroad, then carries out the equipment design and model establishment, and finally conducts sensory carcass assessment and grading and environmental simulation detection experiments through experiments, and uses the colorimeter and beef carcass intelligent grading system to detect the color difference L*, a*, b* values of meat samples in different environments, color space RGB and HSV color parameters, compare the influence of different environments on meat color parameters and grading results, and verify the feasibility of beef carcass grading photography equipment. The results show that the overall values of the equipment group are at a stable level and in line with the sensory evaluation, so the beef carcass grading camera equipment can effectively avoid the influence of external objective factors, such as: light and dark, poor light source, limiter and framing distance. At the same time, it reduces the interference of operators in the classification process and other problems such as the subjective negligence of the operator on the classification results. The project design equipment structure is simple and reliable, automation equipment is easy to operate and low cost, the new beef cattle carcass grading photographic equipment, suitable for promotion and mass production into the market, can improve labor production efficiency, promote the development of local enterprises’ meat industry, increase enterprise income, reduce the production cost of enterprises, to promote the standardization and unification of beef cattle industry grading system.
Functional Polymeric Membranes with Antioxidant Properties for the Colorimetric Detection of Amines

Herein, the ability of highly porous colorimetric indicators to sense volatile and biogenic amine vapors in real time is presented. Curcumin-loaded polycaprolactone porous fiber mats are exposed to various concentrations of off-flavor compounds such as the volatile amine trimethylamine, and the biogenic amines cadaverine, putrescine, spermidine, and histamine, in order to investigate their colorimetric response. CIELAB color space analysis demonstrates that the porous fiber mats can detect the amine vapors, showing a distinct color change in the presence of down to 2.1 ppm of trimethylamine and ca. 11.0 ppm of biogenic amines, surpassing the limit of visual perception in just a few seconds. Moreover, the color changes are reversible either spontaneously, in the case of the volatile amines, or in an assisted way, through interactions with an acidic environment, in the case of the biogenic amines, enabling the use of the same indicator several times. Finally, yet importantly, the strong antioxidant activity of the curcumin-loaded fibers is successfully demonstrated through DPPH● and ABTS● radical scavenging assays. Through such a detailed study, we prove that the developed porous mats can be successfully established as a reusable smart system in applications where the rapid detection of alkaline vapors and/or the antioxidant activity are essential, such as food packaging, biomedicine, and environmental protection.
A global bibliometric and visualized analysis of gait analysis and artificial intelligence research from 1992 to 2022

Gait is an important basic function of human beings and an integral part of life. Many mental and physical abnormalities can cause noticeable differences in a person’s gait. Abnormal gait can lead to serious consequences such as falls, limited mobility and reduced life satisfaction. Gait analysis, which includes joint kinematics, kinetics, and dynamic Electromyography (EMG) data, is now recognized as a clinically useful tool that can provide both quantifiable and qualitative information on performance to aid in treatment planning and evaluate its outcome. With the assistance of new artificial intelligence (AI) technology, the traditional medical environment has undergone great changes. AI has the potential to reshape medicine, making gait analysis more accurate, efficient and accessible. In this study, we analyzed basic information about gait analysis and AI articles that met inclusion criteria in the WoS Core Collection database from 1992–2022, and the VosViewer software was used for web visualization and keyword analysis. Through bibliometric and visual analysis, this article systematically introduces the research status of gait analysis and AI. We introduce the application of artificial intelligence in clinical gait analysis, which affects the identification and management of gait abnormalities found in various diseases. Machine learning (ML) and artificial neural networks (ANNs) are the most often utilized AI methods in gait analysis. By comparing the predictive capability of different AI algorithms in published studies, we evaluate their potential for gait analysis in different situations. Furthermore, the current challenges and future directions of gait analysis and AI research are discussed, which will also provide valuable reference information for investors in this field.
Recent advances of additively manufactured noninvasive kinematic biosensors

The necessity of reliable measurement data assessment in the realm of human life has experienced exponential growth due to its extensive utilization in health monitoring, rehabilitation, surgery, and long-term treatment. As a result, the significance of kinematic biosensors has substantially increased across various domains, including wearable devices, human-machine interaction, and bioengineering. Traditionally, the fabrication of skin-mounted biosensors involved complex and costly processes such as lithography and deposition, which required extensive preparation. However, the advent of additive manufacturing has revolutionized biosensor production by facilitating customized manufacturing, expedited processes, and streamlined fabrication. AM technology enables the development of highly sensitive biosensors capable of measuring a wide range of kinematic signals while maintaining a low-cost aspect. This paper provides a comprehensive overview of state-of-the-art noninvasive kinematic biosensors created using diverse AM technologies. The detailed development process and the specifics of different types of kinematic biosensors are also discussed. Unlike previous review articles that primarily focused on the applications of additively manufactured sensors based on their sensing data, this article adopts a unique approach by categorizing and describing their applications according to their sensing frequencies. Although AM technology has opened new possibilities for biosensor fabrication, the field still faces several challenges that need to be addressed. Consequently, this paper also outlines these challenges and provides an overview of future applications in the field. This review article offers researchers in academia and industry a comprehensive overview of the innovative opportunities presented by kinematic biosensors fabricated through additive manufacturing technologies.
A novel time-frequency analysis method for fault diagnosis based on generalized S-transform and synchroextracting transform

Rotating machinery usually operates under variable-speed conditions, and how to effectively handle nonstationary signal in fault diagnosis is a critical task. The time-frequency analysis (TFA) method is widely used in the processing of nonstationary signal. To improve the time-frequency resolution and clearly identify instantaneous frequency (IF) characteristics, the adaptive generalized S-synchroextracting transform (AGSSET), which is a novel TFA method proposed in this paper. Firstly, a new transform named adaptive generalized S-transform (AGST) is put forward by optimizing the window function of generalized S transform. In this paper, an adaptive window function optimization method based on the frequency spectrum of the vibration signal is introduced, and the energy concentration measure is used to determine the window function’s parameters in AGST. Simultaneously, the synchrony extraction idea is incorporated into the AGST, then the AGSSET is derived. To address more complex IF characteristics, the synchronous extraction operator (SEO) is reconstructed. In the simulation experiment, the GMLC signal model is selected to represent nonstationary signal and to verify the effectiveness of the proposed method. In addition, bearing fault data is also used for fault diagnosis experiments. The results of both numerical simulation and experimental analysis indicate that AGSSET performs well in identifying the time-varying IF characteristic in nonstationary signals. It can also efficiently detect faults with high accuracy and strong stability.
An Adaptive Intrusion Detection System in the Internet of Medical Things Using Fuzzy-Based Learning

The Internet of Medical Things (IoMT) is a growing trend within the rapidly expanding Internet of Things, enhancing healthcare operations and remote patient monitoring. However, these devices are vulnerable to cyber-attacks, posing risks to healthcare operations and patient safety. To detect and counteract attacks on the IoMT, methods such as intrusion detection systems, log monitoring, and threat intelligence are utilized. However, as attackers refine their methods, there is an increasing shift toward using machine learning and deep learning for more accurate and predictive attack detection. In this paper, we propose a fuzzy-based self-tuning Long Short-Term Memory (LSTM) intrusion detection system (IDS) for the IoMT. Our approach dynamically adjusts the number of epochs and utilizes early stopping to prevent overfitting and underfitting. We conducted extensive experiments to evaluate the performance of our proposed model, comparing it with existing IDS models for the IoMT. The results show that our model achieves high accuracy, low false positive rates, and high detection rates, indicating its effectiveness in identifying intrusions. We also discuss the challenges of using static epochs and batch sizes in deep learning models and highlight the importance of dynamic adjustment. The findings of this study contribute to the development of more efficient and accurate IDS models for IoMT scenarios.
Insomnia and potential risk factors during pregnancy

Background: Insomnia during pregnancy adversely affects both mother and newborn, but evidence for its proportion and potential risk factors in Sri Lankan pregnant women is limited. Therefore, this study aimed to determine the proportion and factors associated with insomnia during pregnancy.Methods: A descriptive cross-sectional study was conducted among 404 antenatal women who participated in pregnancysupport groups on Facebook during the COVID-19 pandemic. They responded to a self-administered questionnaire that included the Insomnia Severity Index (ISI) to detect insomnia and questions adapted from the Stanford Sleep Questionnaire and an abbreviated version of the Penn State Worry Questionnaire to determine associated factors. Habitual sleep efficiency was calculated using the Pittsburgh Sleep Quality Index (PSQI). Logistic regression models were used to determine the associations of risk factors with insomnia.Results: The proportion of insomnia overall was 32.7%, with proportions of moderate and severe insomnia being 28% and 1.5%, respectively. The proportion of insomnia was lowest in the 1st trimester (19.2%) and highest in the 3rd trimester (42.8%). The risk factors that were associated with insomnia included age ≥30 years (OR = 1.6, 95% CI 1.09-2.52), third trimester (OR = 3.1, 95% CI 1.49-6.56), overweight or obesity in early pregnancy (OR = 1.8, 95% CI 1.04-3.16), irregular sleep routine (OR = 5.2, 95% CI 3.28-8.42), sleeping on lateral position (OR = 1.6, 95% CI 1.03-2.71), trait of worry (OR = 2.4, 95% CI 1.50-4.02), night back pain (OR = 1.7, 95% CI 1.01-2.91), difficulty in breathing (OR = 2.4, 95% CI 1.37-4.39), heart burn and regurgitation (OR = 1.9, 95% CI 1.24-2.99), and awakening due to foetal movements (OR = 1.8, 95% CI 1.14-2.96). Conclusion: Insomnia during pregnancy was high and may have clinical implications for primary antenatal care practice. Many factors associated with insomnia during pregnancy are modifiable and can form the basis for prevention and management.
Distribution of Woolly Whitefly Aleurothrixus floccosus Maskell on Guava from Tamil Nadu

The distribution, coexistence and natural enemies of the woolly whitefly Aleurothrixus floccosus Maskell (Hemiptera: Aleyrodidae) was assessed on guava (var Lucknow 49) in southern districts of Tamil Nadu viz., Madurai, Dindigul and Virudhunagar during January-July 2023. Identity of A. floccosus was established by the characteristic features on the puparium of the presence of submarginal setae and uninterrupted submarginal fold at the vasiform orifice. Results of the roving surveys from all the surveyed locations indicated that the nymphal population was found to be the highest on the middle canopy (43.75/ 2.5 sq.cm/10 leaves) followed by bottom canopy (27.73) and top canopy (13.10). However, population of eggs and adults were maximum on the top canopy (39.92, 1.95/ 2.5 sq.cm/ 10 leaves) compared to middle (25.91, 1.43) and bottom (10.75, 1.26) canopies. On guava leaves, woolly whitefly was found predominant and cooccurred with the spiralling whitefly Bondars nesting whitefly, rugose spiralling whitefly, two-tailed mealybugs, aphids and scale insects. No promising parasitoids for A. floccosus were present in the surveyed location. Generalist predators, Dichochrysa sp. (Chrysopidae : Neuroptera) ladybird beetles and spiders were found associated with A. floccosus.
Measuring Heat Stress for Human Health in Cities: A Low-Cost Prototype Tested in a District of Valencia, Spain

Nowadays, the measurement of heat stress indices is of principal importance due to the escalating impact of global warming. As temperatures continue to rise, the well-being and health of individuals are increasingly at risk, which can lead to a detrimental effect on human performance and behavior. Hence, monitoring and assessing heat stress indices have become necessary for ensuring the safety and comfort of individuals. Thermal comfort indices, such as wet-bulb globe temperature (WBGT), Tropical Summer Index (TSI), and Predicted Heat Strain (PHS), as well as parameters like mean radiant temperature (MRT), are typically used for assessing and controlling heat stress conditions in working and urban environments. Therefore, measurement and monitoring of these parameters should be obtained for any environment in which people are constantly exposed. Modern cities collect and publish this relevant information following the Smart City concept. To monitor large cities, cost-effective solutions must be developed. This work presents the results of a Heat Stress Monitoring (HSM) system prototype network tested in the Benicalap-Ciutat Fallera district in Valencia, Spain. The scope of this work is to design, commission, and test a low-cost prototype that is able to measure heat stress indices. The Heat Stress Monitoring system comprises a central unit or receiver and several transmitters communicating via radiofrequency. The transmitter accurately measures wind speed, air temperature, relative humidity, atmospheric pressure, solar irradiation, and black globe temperature. The receiver has a 4G modem that sends the data to an SQL database in the cloud. The devices were tested over one year, showing that radio data transmission is reliable up to 700 m from the receiver. The system’s power supply, composed of a Photovoltaic panel and Lithium-ion batteries, provided off-grid capabilities to the transmitter, with a tested backup autonomy of up to 36 days per charge. Then, indicators such as WBGT, TSI, and MRT were successfully estimated using the data collected by the devices. The material cost of a 12-point network is around EUR 2430 with a competitive price of EUR 190 per device.
Long‐term change in precipitation structure over the karst area of Southwest China

This research analyses the long‐term changes in the precipitation structure over the karst area of southwest China, as recorded by 153 national meteorological stations from 1959 to 2009. Study results are as follows: (1) The karst area of southwest China is categorized into six similar precipitation clusters, including two low‐rainfall clusters located in the western and northern areas and four high‐rainfall clusters distributed in the eastern and southern areas. (2) Although the decreasing trend of annual total precipitation is weak, autumn precipitation decreases significantly over the whole study area. The autumn total precipitation decreases significantly at 51% of the stations because the autumn wind and water vapor flux of the study area gradually decreased, and the autumn low‐latitude and mid‐latitude sea surface temperature (SST) of East Asia continues to rise and gradually leads to positive sea anomalies. (3) The number of rainy days decreases at 85.6% of the stations, especially in the central and southeastern regions of the area. Consequently, almost 53% of the total stations are characterized by an increasing precipitation intensity. (4) The occurrence time of the accumulated percentage precipitation in the western mountain areas is usually later than that in the eastern coastal areas, and the occurrence date of accumulated percentage precipitation (DAP) seems to occur increasingly earlier over the whole study area. (5) Light rain occurs more frequently (76% of annual total rainy days) and contributes 25% to annual total precipitation, whereas although heavy rains such as storms occur less frequently at 3% of annual total rainy days, it contributes almost 19% to annual total precipitation. (6) The occurrence and contribution of wet periods (WPs) decrease with an increase in their duration. WPs with short durations (e.g. 1–4 days) tend to be the predominant precipitation events.
The genome sequence of an ichneumonid wasp, Heteropelma amictum (Fabricius, 1775)

We present a genome assembly from an individual female Heteropelma amictum (an ichneumonid wasp; Arthropoda; Insecta; Hymenoptera; Ichneumonidae). The genome sequence is 226.4 megabases in span. Most of the assembly is scaffolded into 10 chromosomal pseudomolecules. The mitochondrial genome has also been assembled and is 20.65 kilobases in length.
Procedures for the approval of oil spill treatment products in the UK

In responseto oil spill incidentsin the UK, counter-pollutionteams use a wide range of remediationand recoveryproducts. It is the policyof the UK to only use such products when necessaryto protect wildlife, fisheiy and amenity interests.As suck a system is required to ensure that only those products that are both effectiveand environmentally acceptableare approvedfor use. Under UK legislationall substancesused for treatingoil spills in the marine environment mustbe approved,Thispaperdescribestie approvalprocess,includingelementsof efficacy and riskassessmentbut focusesprimarilyon the toxicityassessment,The toxicitytests in the approvalschemewere designedfor the assessmentof dispersantsbuthave been Mher developed to enable testing of sorbents, bioremediation and miscellaneous products. Bioremediationproductsalsoundergoadditionaltestingusinga fishspecies, The main approval scheme includestwo test procedures, the sea and rocky shore tests, againstwhichall products are assessed.Productsmust pass both testsbefore an approval for use in UK waterscan be granted,The sea test comparesthe toxicityof a stantid oil (Kuwaitcrude)to the brown shrimp(Crangoncrangon) undermechanicaldispersionand in the sameconditionsaikr treatmentwitha candidateproduct.Aproductthat significantly increasesthetoxicityof the untreatedoilwill failthetest.The rockyshoretest simulatesthe exposureof a representativeshoredweller,the common limpet(Patellavzdgata),to oil or product.In orderto pass the testa productmustnot exhibitgreatertoxicitythan the oil. This paper describesthe toxicitytest protocols in detail and explainsthe test validityand pasdfail criteriaof each. On-goingresearch issuesassociatedwiththe testing of products andthe assessmentof oil spillimpactsare raised. © 2002 WIT Press, Ashurst Lodge, Southampton, SO40 7AA, UK. All rights reserved. Web: www.witpress.com Email witpress@witpress.com Paper from: Oil and Hydrocarbon Spills III, CA Brebbia (Editor). ISBN 1-85312-922-4
Levee Failures in the Sacramento - San Joaquin River Delta: Characteristics and Perspectives

Levee Failures in the Sacramento – San Joaquin River Delta: Characteristics and Perspectives. (December 2011) Frank Hopf, B.S., Lafayette College; M.B.A., Boston University Co-chairs of Advisory Committee: Dr. Christian Brannstrom Dr. Douglas J. Sherman Between 1850 and 1922, agriculturalists built 1,700 kilometers of levees to convert 250,000 hectares of tidal marsh to farmland where the San Joaquin and Sacramento Rivers enter the San Francisco Bay (the Delta). Drained, farmed and isolated from the water channels, the organic soils behind the levees subsided to elevations as low as 8 meters below sea level, turning “levees” into “dams” that hold back water constantly. Engineers built water transfer projects in the mid-20 century, transferring water from the south Delta to 25 million Californians who now rely on the “dams” accidentally converted into supply channels. In 1972, however, a levee failure caused a salt-water intrusion into the Delta, raising the prominence of the polemic Peripheral Canal which, if built would replace the levees in the trans-Delta water transport role. Levee failures in 2004 (the Delta) and 2005 (New Orleans) have re-ignited the debate, fueled by comments made by public officials who warned that the Delta levees posed more risk of failure than did the pre-Katina Louisiana levees. This background motivates two research questions: What are the social perspectives regarding levee failures of the experts managing the Delta; and what is the history of levee failures that might support their perspectives?
MARINE AND ESTUARINE FISHERIES ALONG THE KWAZULU-NATAL COAST: AN INVENTORY AND BRIEF DESCRIPTION

This publication is a compilation of profiles for marine and estuarine fisheries that operate/have operated on the KwaZulu-Natal coast. Profiles for a total of eight fisheries are provided with descriptions of 22 smaller components of the larger fisheries also included. Beside a general description, the following information has also been provided: participation, user profiles, catches, effort, impacts on biodiversity, sustainability, monitoring and data collection, economic values and management strategies used. The profiles are intended to collate current knowledge about the fisheries into a single source to help users, managers and researchers determine the state of the fisheries and to enable the development of effective and informed