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Background: Evidence-based treatments for depression exist but not all patients benefit from them. Efforts to develop predictive models that can assist clinicians in allocating treatments are ongoing, but there are major issues with acquiring the volume and breadth of data needed to train these models. We examined the feasibility, tolerability, patient characteristics, and data quality of a novel protocol for internet-based treatment research in psychiatry that may help advance this field. Methods: A fully internet-based protocol was used to gather repeated observational data from patient cohorts receiving internet-based cognitive behavioural therapy (iCBT) (N = 600) or antidepressant medication treatment (N = 110). At baseline, participants provided > 600 data points of self-report data, spanning socio-demographics, lifestyle, physical health, clinical and other psychological variables and completed 4 cognitive tests. They were followed weekly and completed another detailed clinical and cognitive assessment at week 4. In this paper, we describe our study design, the demographic and clinical characteristics of participants, their treatment adherence, study retention and compliance, the quality of the data gathered, and qualitative feedback from patients on study design and implementation. Results: Participant retention was 92% at week 3 and 84% for the final assessment. The relatively short study duration of 4 weeks was sufficient to reveal early treatment effects; there were significant reductions in 11 transdiagnostic psychiatric symptoms assessed, with the largest improvement seen for depression. Most participants (66%) reported being distracted at some point during the study, 11% failed 1 or more attention checks and 3% consumed an intoxicating substance. Data quality was nonetheless high, with near perfect 4-week test retest reliability for self-reported height (ICC = 0.97). Conclusions: An internet-based methodology can be used efficiently to gather large amounts of detailed patient data during iCBT and antidepressant treatment. Recruitment was rapid, retention was relatively high and data quality was good. This paper provides a template methodology for future internet-based treatment studies, showing that such an approach facilitates data collection at a scale required for machine learning and other data-intensive methods that hope to deliver algorithmic tools that can aid clinical decision-making in psychiatry., BMC Psychiatry, 23 (1), ISSN:1471-244X

Tightly connected symptom networks have previously been linked to treatment resistance, but most findings come from small sample studies comparing single responder vs. non-responder cross-sectional networks. We aimed to estimate the association between baseline network connectivity and treatment response in a large sample and benchmark its prognostic value against baseline symptom severity and variance. N=40,518 patients receiving treatment for depression in routine care in England from 2015-2020 were analysed. Cross-sectional networks were constructed using the Patient Health Questionnaire-9 for responders and non-responders (N=20,259 each). To conduct parametric tests investigating the contribution of mean and variance to connectivity differences, networks were constructed for 160 independent subsamples of responders and non-responders (80 each, n=250 per sample). The baseline network of non-responders was more connected than responders (3.15 vs 2.70, S=0.44, P

A reliable forecasting model is required for photovoltaic (PV) power output because solar energy is highly volatile. Another driver for the need of a reliable forecasting model is concept drift, which means that the statistical properties of the data change over time. In this paper, an online forecasting method to handle concept drift is proposed. First, the problem of forecasting in batch learning is transformed into a forecasting in online learning setting. Then, an online learning algorithm is applied, which is good for handling concept drift. Through experiments using the real‐world data, it is shown that the method noticeably improves performance compared to the case where a trained model is used. Under various concept drift scenarios, the method improves performance by up to 87.3%. It is also shown that the re‐training method (a representative existing method) has several limitations. This method requires several issues to be solved, such as selection of a proper window size, and this is evident through results showing different performance under different settings. In contrast, the method shows a reliable and desirable performance under various concept drift scenarios and thus outperforms the re‐training method. The method improves performance by up to 79%.

Antiresorptives are the most widely prescribed drugs for the treatment of osteoporosis. They are also used in malignant bone metastases, multiple myeloma, and Paget's disease, and provide therapeutic efficacy on those diseases. However, it was reported that the occurrence of osteonecrosis of the jaw (ONJ) could be related to antiresorptive exposures, and there have been many cases regarding this issue. Therefore, a clearer definition and treatment guidelines were needed for this disease. The American Society for Bone and Mineral Research and the Amnerican Association of Oral and Maxillofacial Surgeons reported statements on bisphosphonate-related ONJ (BRONJ), and a revised version was recently presented. In the revised edition, the diagnosis BRONJ was changed to medication-related ONJ (MRONJ), which reflects consideration of the fact that ONJ also occurs for denosumab, a bone resorption inhibitor of the receptor activator of the nuclear factor-κB ligand antibody family, and bevacizumab, an anti-angiogenesis inhibitor. The Korean Society for Bone and Mineral Research and the Korean Association of Oral and Maxillofacial Surgeons had collectively formed a task force for the preparation of an official statement on MRONJ based on a previous position paper in 2015. The task force reviewed current knowledge and coordinated dental and medical opinions to propose the guideline customized for the local Korean situation.

The aim of this study was to compare the effect of using depth of invasion (DOI) versus tumor thickness (TT) as a prognostic factor for early-stage oral squamous cell carcinoma (OSCC). A total of 57 patients with early-stage OSCC treated surgically from 2009 to 2014 at our institution were reviewed retrospectively. Histopathological measurement of DOI and TT was performed. The validation of DOI and TT as prognostic factors was conducted using a Kaplan–Meier survival analysis. TT had no association with disease-specific survival (DSS) or progression-free survival (PFS) in this cohort; however, increased DOI was significantly associated with decreased DSS but not correlated to decreased PFS. The T category of the 7th edition of AJCC was statistically associated with both DSS and PFS; however, the T category of the 8th edition of the AJCC was only associated with DSS. In this study group, TT could not be used as a prognostic factor, and DOI was not by itself sufficient to predict prognosis for early-stage OSCC. The T category in AJCC 8th Edition cannot be considered the sole prognostic factor for early OSCC, so additional prognostic factors may need to be considered.

At present, in Korea, due to developments in medicine and technology and an increasing mean lifespan, the expected lifetime for elderly people is increasing (at 70 years, the expected additional lifespan is 14.8 years for males and 18.3 years for females). However, among all causes of death, malignant neoplasm is ranked first for all ages. Further, the incidence rate of oral cancer tends to increase with age. Thus, oral and maxillofacial surgeons have increased opportunity to experience the 'oldest old' patients with oral cancer. Elderly patients commonly have several comorbidities, poor general condition, limited socioeconomic support, fear of various postoperative complications, and perception of short for the rest of their life. In this situation, the patient, caregiver, and surgeon often choose undergraded treatment rather than standard treatment for oral squamous cell carcinoma owing to patient age. In elderly patients with oral cancer, ablation of tumor or reconstructive surgery is challenging for surgeons. Oral and maxillofacial surgeons must evaluate carefully the patient's medical condition and make a decision regarding treatment plans after sufficient discussion with patient and caregivers. We review the literature to consider the factors involved for deciding on a treatment plan regarding surgery in elderly patients with oral cancer.

The berthing velocity is the factor that has the greatest influence on the berthing energy. For the vessel to berth safely, it should not exceed the appropriate berthing velocity. In addition, when the vessel is berthing, it should be berthed with berthing energy smaller than the energy absorption of the fender. This study intends to derive the allowable berthing velocity by ship size considering the berthing capacity. When a small vessel berth, the allowable berthing velocity is greater than when a relatively large vessel berths. In this study, the extrapolated velocity is defined as the relative value of the ship’s berthing velocity when considering the ship's size and the berthing capacity. A regression equation for the allowable berthing velocity by ship size was derived by calculating the designed berthing energy for each fender performance. It was also verified whether any ships were exceeding the allowable berthing velocity by comparing it with the measured data for each jetty. In addition, the extrapolated velocity was proposed using the regression equation, and as a result of applying the measured data, 11 ships exceeded the designed velocity in jetty 1, but it was confirmed that all ships were safely berthed in jetty 2,3. Therefore, the target pier of this study was evaluated as a pier where ships can be berthed safely. A safer berthing velocity operation guideline can be suggested if the allowable berthing velocity by ship size is analyzed and utilized at various piers. Extrapolated velocity can also be used for risk analysis of berthing.

High-resolution liquid chromatography–tandem mass spectrometry (LC--MS-MS)-based machine learning models are constructed to address the analytical challenge of identifying unknown controlled substances and new psychoactive substances (NPSs). Using a training set composed of 770 LC–MS-MS barcode spectra (with binary entries 0 or 1) obtained generally by high-resolution mass spectrometers, three classification machine learning models were generated and evaluated. The three models are artificial neural network (ANN), support vector machine (SVM) and k-nearest neighbor (k-NN) models. In these models, controlled substances and NPSs were classified into 13 subgroups (benzylpiperazine, opiate, benzodiazepine, amphetamine, cocaine, methcathinone, classical cannabinoid, fentanyl, 2C series, indazole carbonyl compound, indole carbonyl compound, phencyclidine and others). Using 193 LC–MS-MS barcode spectra as an external test set, accuracy of the ANN, SVM and k-NN models were evaluated as 72.5%, 90.0% and 94.3%, respectively. Also, the hybrid similarity search (HSS) algorithm was evaluated to examine whether this algorithm can successfully identify unknown controlled substances and NPSs whose data are unavailable in the database. When only 24 representative LC–MS-MS spectra of controlled substances and NPSs were selectively included in the database, it was found that HSS can successfully identify compounds with high reliability. The machine learning models and HSS algorithms are incorporated into our home-coded artificial intelligence screener for narcotic drugs and psychotropic substances standalone software that is equipped with a graphic user interface. The use of this software allows unknown controlled substances and NPSs to be identified in a convenient manner.

Background The potential risk of coronavirus disease 2019 (COVID-19) transmission from asymptomatic COVID-19 patients is a concern in dental practice. However, the impact of this risk is not well documented to date. This report describes our dental clinical experience with patients who did not exhibit symptoms of COVID-19 but were later confirmed as positive for COVID-19. Case presentation Of the 149,149 patients who visited the outpatient clinic of KNUDH and the 3291 patients who visited the Oral and Maxillofacial Surgery Clinic of KNUH, 3 were later confirmed as having COVID-1 between 1 February 2020 and 28 February 2021. Owing to close contact with these patients during their treatments, 46 dental and medical staff had to undergo quarantine from the date of the patients’ confirmation of COVID-19 infection. Conclusion The presented cases showed the potential existence of asymptomatic COVID-19 patients after dental treatment with aerosol-generating procedures. Clinicians should be aware of the infection prevention measures and try to protect healthcare personnel from secondary infection of COVID-19 during dental treatments.

Background This study aimed to analyze the impact of COVID-19 on oral and maxillofacial fracture in Daegu by comparing the demographic data in 2019 and 2020, retrospectively. We collected data from all patients having trauma who visited the emergency room for oral and maxillofacial fractures. Methods This retrospective study was based on chart review of patients who visited the emergency department of Kyungpook National University Hospital in Daegu, South Korea from January 1, 2019, to December 31, 2020. We conducted a comparative study for patients who presented with maxillofacial fractures with occlusal instability during pre-COVID-19 era (2019) and COVID-19 era (2000) with demographics and pattern of injuries. Results After the outbreak of COVID-19, the number of monthly oral and maxillofacial fractures, especially sports-related oral and maxillofacial fractures, decreased significantly. Also, the number of alcohol-related fractures increased significantly. In addition, as the number of monthly confirmed cases of COVID-19 increases, the incidence of fracture among these cases tends to decrease. Conclusions The COVID-19 pandemic has changed the daily life in Korea. Identifying the characteristics of patients having trauma can provide a good lead to understand this long-lasting infectious disease and prepare for future outbreaks.

This paper studies the dynamic relationship between ship prices and operating profits by using the fact that these two factors are cointegrated. To conduct an empirical analysis, we select Panamax ...

The prognostic implication of cardiac troponin I (cTnI) values for the determination of the magnitude or duration of cause-specific death risk is limited. We included consecutive patients with maximal cTnI values within 24 h of their emergency department visits. Multivariate analyses using variables selected by the Bayesian information criterion were performed to investigate the impact of cTnI on the event rate, time-dependent risk, and dose-dependent risk of cardiovascular or non-cardiovascular death within 360 days. There were 5472 (14.9%) all-cause deaths including 881 (2.4%) cardiovascular deaths and 4591 (12.5%) non-cardiovascular deaths. In patients with positive cTnI, defined as the ≥ 99th percentile of the upper normal limit, the cumulative risk of cardiac and non-cardiac death was 4.4- and 1.4-fold higher, respectively, than that of negative cTnI, respectively. In the competing risk analysis, positive cTnI was linked to 2.4- and 1.2-fold higher risks of cardiovascular and non-cardiovascular death, respectively. The cTnI value showed a positive relationship with the risk of both cardiovascular and non-cardiovascular deaths. In the time-dependent risk analysis, the excess risk of cardiovascular death was mostly evident in the first few weeks. Higher cTnI value was associated with an increased risk of both cardiovascular and non-cardiovascular death, especially which was in the early period.

A pilot guides a ship through a safe waterway based on extensive experience and knowledge of the region for piloting so that the ship can berth quickly and safely. There are insufficient studies on pilots who play crucial roles in pilotage, and most of the available studies have focused on psychological stress or tension. In this study, we group pilots through quantitative analysis of data to help in the safety management of pilots. In particular, berthing velocity and berthing energy were employed as basic data, and the mean and standard deviation values for each pilot after preprocessing were used for analysis. As a result of using the agglomerative clustering algorithm, we could group pilots into three types: cautious, efficient, and hazardous. Further, analysis of variance (ANOVA) showed that there was a significant difference between the cautious and hazardous types.