AI-based betting anomaly detection system to ensure fairness in sports and prevent illegal gambling.

This study develops a solution to sports match-fixing using various machine-learning models to detect match-fixing anomalies, based on betting odds. We use five models to distinguish between normal and abnormal matches: logistic regression (LR), random forest (RF), support vector machine (SVM), the k-nearest neighbor (KNN) classification, and the ensemble model-a model optimized from the previous four. The models classify normal and abnormal matches by learning their patterns using sports betting odds data. The database was developed based on the world football league match betting data of 12 betting companies, which offered a vast collection of data on players, teams, game schedules, and league rankings for football matches. We develop an abnormal match detection model based on the data analysis results of each model, using the match result dividend data. We then use data from real-time matches and apply the five models to construct a system capable of detecting match-fixing in real time. The RF, KNN, and ensemble models recorded a high accuracy, over 92%, whereas the LR and SVM models were approximately 80% accurate. In comparison, previous studies have used a single model to examine football match betting odds data, with an accuracy of 70-80%.

Development of a Non-Contact Sensor System for Converting 2D Images into 3D Body Data: A Deep Learning Approach to Monitor Obesity and Body Shape in Individuals in Their 20s and 30s.

This study demonstrates how to generate a three-dimensional (3D) body model through a small number of images and derive body values similar to the actual values using generated 3D body data. In this study, a 3D body model that can be used for body type diagnosis was developed using two full-body pictures of the front and side taken with a mobile phone. For data training, 400 3D body datasets (male: 200, female: 200) provided by Size Korea were used, and four models, i.e., 3D recurrent reconstruction neural network, point cloud generative adversarial network, skinned multi-person linear model, and pixel-aligned impact function for high-resolution 3D human digitization, were used. The models proposed in this study were analyzed and compared. A total of 10 men and women were analyzed, and their corresponding 3D models were verified by comparing 3D body data derived from 2D image inputs with those obtained using a body scanner. The model was verified through the difference between 3D data derived from the 2D image and those derived using an actual body scanner. Unlike the 3D generation models that could not be used to derive the body values in this study, the proposed model was successfully used to derive various body values, indicating that this model can be implemented to identify various body types and monitor obesity in the future.

The impact of the COVID-19 pandemic on in-hospital mortality in patients admitted through the emergency department.

OBJECTIVE: The COVID-19 pandemic might have adversely affected outcomes of patients in emergency departments (EDs). The aim of this study is to evaluate the impact of the COVID-19 pandemic on in patients admitted through the emergency department. METHODS: This study is a single-center, retrospective, observational cohort study. We compared the prognosis of patients admitted through the ED before the COVID-19 pandemic (November 2018 to June 2019) and after COVID-19 (November 2020 to June 2021). The primary outcome was in-hospital mortality. Multivariable logistic regression analysis was performed to determine whether the COVID-19 pandemic was independently associated with patient prognosis. RESULTS: The number of patients admitted through the ED before and after COVID-19 was 5,333 and 4,625, respectively. The mean ED length of stay before and after COVID-19 was 401 and 442 minutes, respectively (P<0.001). The number of in-hospital deaths before and after COVID-19 were 269 (5.0%) and 322 (7.0%), respectively (P<0.001). Multivariable logistic regression analysis showed that the COVID-19 period was significantly associated with higher in-hospital mortality (adjusted odds ratio, 1.37; 95% confidence interval, 1.12-1.67; P=0.002). CONCLUSION: In the COVID-19 period, in-hospital mortality increased compared to that before COVID-19 among hospitalized ED patients.

Comparison of detection performance of soft tissue calcifications using artificial intelligence in panoramic radiography.

Artificial intelligence (AI) is limited to teeth and periodontal disease in the dental field, and is used for diagnosis assistance or data analysis, and there has been no research conducted in actual clinical situations. So, we created an environment similar to actual clinical practice and conducted research by selecting three of the soft tissue diseases (carotid artery calcification, lymph node calcification, and sialolith) that are difficult for general dentists to see. Therefore, in this study, the accuracy and reading time are evaluated using panoramic images and AI. A total of 20,000 panoramic images including three diseases were used to develop and train a fast R-CNN model. To compare the performance of the developed model, two oral and maxillofacial radiologists (OMRs) and two general dentists (GDs) read 352 images, excluding the panoramic images used in development for soft tissue calcification diagnosis. On the first visit, the observers read images without AI; on the second visit, the same observers used AI to read the same image. The diagnostic accuracy and specificity for soft tissue calcification of AI were high from 0.727 to 0.926 and from 0.171 to 1.000, whereas the sensitivity for lymph node calcification and sialolith were low at 0.250 and 0.188, respectively. The reading time of AI increased in the GD group (619 to 1049) and decreased in the OMR group (1347 to 1372). In addition, reading scores increased in both groups (GD from 11.4 to 39.8 and OMR from 3.4 to 10.8). Using AI, although the detection sensitivity of sialolith and lymph node calcification was lower than that of carotid artery calcification, the total reading time of the OMR specialists was reduced and the GDs reading accuracy was improved. The AI used in this study helped to improve the diagnostic accuracy of the GD group, who were not familiar with the soft tissue calcification diagnosis, but more data sets are needed to improve the detection performance of the two diseases with low sensitivity of AI.

Tooth-Related Disease Detection System Based on Panoramic Images and Optimization Through Automation: Development Study.

BACKGROUND: Early detection of tooth-related diseases in patients plays a key role in maintaining their dental health and preventing future complications. Since dentists are not overly attentive to tooth-related diseases that may be difficult to judge visually, many patients miss timely treatment. The 5 representative tooth-related diseases, that is, coronal caries or defect, proximal caries, cervical caries or abrasion, periapical radiolucency, and residual root can be detected on panoramic images. In this study, a web service was constructed for the detection of these diseases on panoramic images in real time, which helped shorten the treatment planning time and reduce the probability of misdiagnosis. OBJECTIVE: This study designed a model to assess tooth-related diseases in panoramic images by using artificial intelligence in real time. This model can perform an auxiliary role in the diagnosis of tooth-related diseases by dentists and reduce the treatment planning time spent through telemedicine. METHODS: For learning the 5 tooth-related diseases, 10,000 panoramic images were modeled: 4206 coronal caries or defects, 4478 proximal caries, 6920 cervical caries or abrasion, 8290 periapical radiolucencies, and 1446 residual roots. To learn the model, the fast region-based convolutional network (Fast R-CNN), residual neural network (ResNet), and inception models were used. Learning about the 5 tooth-related diseases completely did not provide accurate information on the diseases because of indistinct features present in the panoramic pictures. Therefore, 1 detection model was applied to each tooth-related disease, and the models for each of the diseases were integrated to increase accuracy. RESULTS: The Fast R-CNN model showed the highest accuracy, with an accuracy of over 90%, in diagnosing the 5 tooth-related diseases. Thus, Fast R-CNN was selected as the final judgment model as it facilitated the real-time diagnosis of dental diseases that are difficult to judge visually from radiographs and images, thereby assisting the dentists in their treatment plans. CONCLUSIONS: The Fast R-CNN model showed the highest accuracy in the real-time diagnosis of dental diseases and can therefore play an auxiliary role in shortening the treatment planning time after the dentists diagnose the tooth-related disease. In addition, by updating the captured panoramic images of patients on the web service developed in this study, we are looking forward to increasing the accuracy of diagnosing these 5 tooth-related diseases. The dental diagnosis system in this study takes 2 minutes for diagnosing 5 diseases in 1 panoramic image. Therefore, this system plays an effective role in setting a dental treatment schedule.

Development of an Obesity Information Diagnosis Model Reflecting Body Type Information Using 3D Body Information Values.

This study uses various body values (length, circumference, and volume) that can be derived from 3D data to determine variables and areas that substantially affect obesity and suggests guidelines for diagnosing obesity that are more elaborate than existing obesity indices. Body data for 170 participants (87 men and 73 women aged 20-30 years) are collected for the chest, abdomen, hips, and arms/legs. A 3D scanner, which can produce accurate body point results, and dual-energy X-ray (DEXA), which can accurately determine the fat percentage, are used to derive fat rates for each body part. The fat percentage and total fat percentage for each body part are used as learning data. For the derived data, the eigenvalue for each body part is derived using a principal component analysis, and the following four clusters are created for each part: underweight, normal, overweight, and obese. A comparison with the obesity index, which diagnoses obesity based on the cluster model, showed that the accuracy of the model proposed in this study is higher at 80%. Therefore, this model can determine the body information necessary for accurate obesity diagnosis and be used to diagnose obesity with greater accuracy than obesity indices without a body fat measurement machine such as DEXA.

Long-term nationwide assessment of polychlorinated dibenzo-p-dioxins/dibenzofurans and dioxin-like polychlorinated biphenyls ambient air concentrations for ten years in South Korea.

In this study, seasonal/regional variations of Polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/DFs) and dioxin like-polychlorinated biphenyls in the ambient air were monitored for ten years (2008-2017) using a high volume air sampler. As a result of strict regulation enforced by Korea Ministry of Environment in 2008, PCDD/DFs concentrations in the ambient air decreased from 0.051 pg I-TEQ Sm-3 in 2009 to 0.014 pg I-TEQ Sm-3 in 2017 which was comparably associated with cut-down of their emission sources from 880.2 g I-TEQ Sm-3 in 2001 to 24.2 g I-TEQ Sm-3 in 2015; revealing that it was only 2.7% against that of 2001. In 2017, mean TEQ concentration level of PCDD/DFs in the air of South Korea was quite low in comparison to its ambient environmental standards of 0.6 pg I-TEQ Sm-3 for PCDD/DFs. Particularly, the sum of PCDD/DFs in the background revealed the lowest level, however, the fraction of octachlorodibenzodioxin among other isomers exposed at the highest level in this study, suggesting that the ambient air quality in the background being studied was severely and persistently impaired by inflowing unknown sources of any possible anthropogenic transboundary migratory air pollutants. Moreover, this study conducted the scientific analysis of the long-term variations in the ambient air and emission sources using principal component analysis. From this of 10 years long-term nationwide assessments for the PCDD/DFs and dl-PCBs in the ambient air, it is possible to prove that South Korean environmental policy to manage POPs has been successfully conducted for the last ten years.

Redox-mediator-free degradation of sulfathiazole and tetracycline using Phanerochaete chrysosporium.

The removal of two of the most commonly used antibiotics, tetracycline (TC) and sulfathiazole (STZ), using laccase-producing Phanerochaete chrysosporium was studied in liquid-phase batch experiments in the absence of any synthetic redox mediator. The removal of STZ and TC from single antibiotic spikes varied from 97.8% to 15.4% and 98.8% to 31%, respectively, with increasing initial doses of 10-250 mg L-1 within 14 days of incubation. The enzyme activity of P. chrysosporium was only minimally influenced by the concentrations of these antibiotics. The degradation of antibiotics initiated before an appreciable extracellular enzyme activity was noted in the fungal culture. The appearance of low-molecular weight molecular fragments from parent antibiotics in liquid chromatography-mass spectrometry confirmed the biodegradation process.

Quantification of residual antibiotics in cow manure being spread over agricultural land and assessment of their behavioral effects on antibiotic resistant bacteria.

Antibiotic resistant bacteria (ARB) in livestock manure used as fertilizer and spread over agriculture land, may pose a threat to the health of humans. Considering this, the concentrations of tetracycline (TC), oxytetracycline (OTC), and sulfathiazole (STZ) in the surface soil were quantified using LC-MS. These antibiotics have been used in livestock and are found in fertilizer produced from livestock excretions. Species of ABR were identified using 16S rDNA. Soil samples were collected at depths of 0, 7, and 15 cm from farmland in Incheon (South Korea). In the surface soil, three compounds were detected: TC (17.74 µg/kg), OTC (0.78 µg/kg), and STZ (0.23 µg/kg). However, except for STZ, antibiotics were not detected in the deeper samples. Overall, TC can form a chelated complex with cations, which consequently enhances its adsorption to the organic matter and metals in soil. This property can significantly reduce the mobility of TC (to lower than that of STZ). The result of 16S rDNA gene analysis indicated that Pseudomonas spp., Arthrobacter spp., and Rhodococcus spp. showed persistent resistance to the three antibiotics tested. DNA quantification results revealed strong resistance of Pseudomonas spp. to STZ, whereas Arthrobacter spp. and Rhodococcus spp. had resistance to TC and OTC. Antibiotics biodegradation suggested ability of ARB to grow in soil samples in presence of residual antibiotics during 13 days incubation. The concentrations of STZ, TC, and OTC reduced as much as 23.53, 35.60 and 66.88%, respectively.

Assessment of isokinetic muscle function in Korea male volleyball athletes.

Volleyball players performed numerous repetitions of spike actions, which uses and requires strong and explosive force, and control of the muscles of the shoulder, lower back, and legs. Muscle imbalance is one of the main causes of sport injuries. The purpose of this study was to assess isokinetic muscle functions in male volleyball players. We thus aim to accurately evaluate their muscle functions, and identify the best training strategy to achieve optimal muscle strength balance in future training programs. The participants in this study consisted of 14 male volleyball players. Muscle strength was measured using the isokinetic dynamometer. Muscle strength was evaluated in terms of peak torque and average power, calculated from five repeated measurements at an angular speed of 60°/sec. Three players who were left attackers showed shoulder imbalance, four players showed trunk joint imbalance, nine players had knee joint of extension/flexion imbalance and four players showed left/right imbalance. The results showed that the number of volleyball players with differences between the strength of the bilateral knee muscles, and between the strength of the hamstrings and quadriceps muscles was higher than the number of players with differences between the strength of the shoulder internal and external rotation muscles, and higher than the number of players with differences between the strength of the lower back extension and flexion muscles.

Effect of startup circuit exercise on derivatives reactive oxygen metabolites, biological antioxidant potential levels and physical fitness of adolescents boys with intellectual disabilities.

The purpose of this study was to examine the effect of starup circuit exercise program on derivatives reactive oxygen metabolite (d-ROM) and biological antioxidant potential (BAP) levels and physical fitness of adolescents with intellectual disabilities, and to sugesst exercise programs to promote the health and physical development of such adolescents. Twelve students with intellectual disabilities were divided into two groups; circuit exercise group (CE group: n=6; age, 14.83±0.98 years; height, 163.83±5.78 cm; body mass, 67.08±3.32 kg; %Fat, 25.68±2.42), control group (CON group: n=6; age: 15.00±0.63 years; height, 162.33±4.41 cm; body mass, 67.50±3.62 kg; %Fat, 26.96±2.06). The CE group performed the CE program 4 times a week over a 12-week period. The CON group maintained their activities of daily living. The following were measured before and after intervention: physical fitness by before and after the completion of the training programm, and were measured and blood samples were assessed. The results of the study indicate that the 12-week CE program increased significantly physical fitness (P<0.05). Furthermore, This study proved that the CE program improved physical fitness, and reduced the d-ROM levels, and increased the BAP levels of the adolescents with intellectual disabilities. Therefore, it may enhance the health and physical development of adolescents boys with intellectual disabilities.

Studies on influence and fate of carbamazepine in anaerobic digestion of sludge.

Increased consumption of pharmaceutical compounds compounded by their persistence in biological treatment processes and potential toxicity is becoming a serious concern. The aim of the present study was to investigate the fate of an antiepileptic drug, carbamazepine (CBZ), in anaerobic digestion process and its impact on methanogenic metabolism. Biochemical methane potential of CBZ with or without glucose was studied for 40 days in designed batch experiments. About 67.98% and 66.37% of spiked CBZ (about 100 µg l(-1)) were removed during this period from glucose amended or unamended sets, respectively. Loss of CBZ through adsorption onto suspended particles, as in sterilized seed sludge control (16.98%), was significantly lower in comparison to its biotic counterparts (P = 0.002 and P = 0.003). Analysis of methane or biogas production revealed no inhibitory effect of CBZ toward methanogenic process at its tested concentration. Differences in cumulative methane yields between glucose containing sets with or without CBZ were insignificant (P = 0.885). This study suggests that any residual CBZ concentration lower than the present study, if detected in waste-water, might not significantly affect the methanogenic process.

Degradation of the long-resistant pharmaceutical compounds carbamazepine and diatrizoate using mixed microbial culture.

The microbial degradation of two recalcitrant pharmaceutical compounds, carbamazepine (CBZ) and diatrizoate (DTZ), was studied in laboratory batch experiments. We used a defined mixed microbial culture comprising four distinct microbial species that were previously known to have high decomposition capacity toward recalcitrant substances. Biological decomposition in liquid phase cultures for either CBZ or DTZ, or in a combination of the two, was conducted for 12 days. DTZ and CBZ were degraded by 43.2% and 60%, respectively from an initial concentration of 100 µg L(-1). When degradation was assessed using a mixture of the two compounds, the initial degradation rates of CBZ and DTZ were lower than those observed in the single-compound study. However, the final cumulative removal efficiency was very similar. The extent of dissolved organic carbon (DOC) removal was correlated with the degradation of the pharmaceuticals.

Evaluating physical and perceptual responses to exergames in Chinese children.

PURPOSE: The primary objective of this study was to examine whether exergames could help children reach the recommendations for PA and cardiorespiratory fitness regarding exercise intensity. Differences in perceived physical exertion, EE, VO2, and HR between normal weight (NW) and overweight (OW) children participating in exergames were also examined. METHODS: Twenty-one children (age: 10.45 ± 0.88) were assessed for EE, VO2 and HR during rest, in a maximal treadmill test, and while playing different exergames. Ratings of perceived exertion (RPE) (category range: 0 to 10) were also measured during exergaming. Three types of exergames were examined: running, table tennis, and dancing. These games were either performed on a Chinese game console, I-Dong, or another well-developed Western game console (Sony PlayStation 3 or Nintendo Wii). RESULTS: Exergaming resulted in EE (kcal/min) from 2.05-5.14, VO2 (mL/kg/min) from 9.98-25.54, and HR (beats per minute) from 98.05-149.66. Children reported RPE ranging from 1.29 to 5.29. The Chinese exergame, I-Dong Running, was the only game in which children reached a moderate intensity and met the recommended minimum VO2reserve (50%) for cardiorespiratory fitness. CONCLUSION: Exergames could provide alternative opportunities to enhance children's physical activity. They could be used as light-to-moderate PA, and with exergames, children can even reach the recommended intensity for developing and maintaining cardiorespiratory fitness.

Comparative enzyme inhibitive methanol production by Methylosinus sporium from simulated biogas.

Methane in a simulated biogas converting to methanol under aerobic condition was comparatively assessed by inhibiting the activity of methanol dehydrogenase (MDH) of Methylosinus sporium using phosphate, NaCl, NH4Cl or EDTA in their varying concentrations. The highest amount of methane was indistinguishably diverted at the typical conditions regardless of the types of inhibitors: 35°C and pH 7 under a 0.4% (v/v) of biogas, specifically for <40 mM phosphate, 50 mM NaCl, 40 mM NH4Cl or 150 µM EDTA. The highest level of methanol was obtained for the addition of 40 mM phosphate, 100 mM NaCl, 40 mM NH4Cl or 50 µM EDTA. In other words, 0.71, 0.60, 0.66 and 0.66 mmol methanol was correspondingly generated by the oxidation of 1.3, 0.67, 0.74 and 1.3 mmol methane. It gave a methanol conversion rate of 54.7%, 89.9%, 89.6% and 47.8%, respectively. Among them, the maximum rate of methanol production was observed at 6.25 µmol/mg h for 100 mM NaCl. Regardless of types or concentrations of inhibitors differently used, methanol production could be nonetheless identically maximized when the MDH activity was limitedly hampered by up to 35%.

Partial oxidative conversion of methane to methanol through selective inhibition of methanol dehydrogenase in methanotrophic consortium from landfill cover soil.

Using a methanotrophic consortium (that includes Methylosinus sporium NCIMB 11126, Methylosinus trichosporium OB3b, and Methylococcus capsulatus Bath) isolated from a landfill site, the potential for partial oxidation of methane into methanol through selective inhibition of methanol dehydrogenase (MDH) over soluble methane monooxygenase (sMMO) with some selected MDH inhibitors at varied concentration range, was evaluated in batch serum bottle and bioreactor experiments. Our result suggests that MDH activity could effectively be inhibited either at 40 mM of phosphate, 100 mM of NaCl, 40 mM of NH4Cl or 50 µM of EDTA with conversion ratios (moles of CH3OH produced per mole CH4 consumed) of 58, 80, 80, and 43 %, respectively. The difference between extent of inhibition in MDH activity and sMMO activity was significantly correlated (n = 6, p < 0.05) with resultant methane to methanol conversion ratio. In bioreactor study with 100 mM of NaCl, a maximum specific methanol production rate of 9 µmol/mg h was detected. A further insight with qPCR analysis of MDH and sMMO coding genes revealed that the gene copy number continued to increase along with biomass during reactor operation irrespective of presence or absence of inhibitor, and differential inhibition among two enzymes was rather the key for methanol production.

Modified uvulopalatopharyngoplasty for the treatment of obstructive sleep apnea-hypopnea syndrome: resection of the musculus uvulae.

OBJECTIVE: To assess the outcome of a modified uvulopalatopharynbgoplasty (UPPP) technique with preservation of the uvula mucosa and partial resection of the musculus uvula. STUDY DESIGN AND METHODS: A prospective randomized controlled trial. Sixteen male patients underwent a classic UPPP, and another 16 male patients underwent a modified UPPP. The parameters evaluated were the subjective symptom score, the Pittsburgh Sleep Quality Index (PSQI), the Epworth Sleepiness Scale (ESS), the Stanford Sleepiness Scale (SSS), and polysomnography results. RESULTS: Postoperative snoring, apnea, morning headache, daytime sleepiness, pharyngeal foreign body sensation, and global discomfort were not significantly different between the two groups. Among seven subjective measures of sleep quality from the PSQI, the subjective sleep quality was significantly improved in both groups. Postoperatively, the SSS was not significantly changed in both groups; however, the ESS was significantly improved in both groups. The polysomnographic findings showed a statistically significantly improvement in the apnea index and the apnea-hypopnea index. CONCLUSION: Although the modified group did not have more profound improvement in sleep quality and decreased postoperative pharyngeal discomfort, modified UPPP was an effective surgical method for the treatment of obstructive sleep apnea-hypopnea syndrome.

Decomposition of 1,4-dioxane by advanced oxidation and biochemical process.

This study was undertaken to determine the optimal decomposition conditions when 1,4-dioxane was degraded using either the AOPs (Advanced Oxidation Processes) or the BAC-TERRA microbial complex. The advanced oxidation was operated with H2O2, in the range 4.7 to 51 mM, under 254 nm (25 W lamp) illumination, while varying the reaction parameters, such as the air flow rate and reaction time. The greatest oxidation rate (96%) of 1,4-dioxane was achieved with H2O2 concentration of 17 mM after a 2-hr reaction. As a result of this reaction, organic acid intermediates were formed, such as acetic, propionic and butyric acids. Furthermore, the study revealed that suspended particles, i.e., bio-flocs, kaolin and pozzolan, in the reaction were able to have an impact on the extent of 1,4-dioxane decomposition. The decomposition of 1,4-dioxane in the presence of bio-flocs was significantly declined due to hindered UV penetration through the solution as a result of the consistent dispersion of bio-particles. In contrast, dosing with pozzolan decomposed up to 98.8% of the 1,4-dioxane after 2 hr of reaction. Two actual wastewaters, from polyester manufacturing, containing 1,4-dioxane in the range 370 to 450 mg/L were able to be oxidized by as high as 100% within 15 min with the introduction of 100:200 (mg/L) Fe(II):H202 under UV illumination. Aerobic biological decomposition, employing BAC-TERRA, was able to remove up to 90% of 1,4-dioxane after 15 days of incubation. In the meantime, the by-products (i.e., acetic, propionic and valeric acid) generated were similar to those formed during the AOPs investigation. According to kinetic studies, both photo-decomposition and biodegradation of 1,4-dioxane followed pseudo first-order reaction kinetics, with k = 5 x 10(-4) s(-1) and 2.38 x 10(-6) s(-1), respectively. It was concluded that 1,4-dioxane could be readily degraded by both AOPs and BAC-TERRA, and that the actual polyester wastewater containing 1,4-dioxane could be successfully decomposed under the conditions of photo-Fenton oxidation.