Balanced Set Research Articles

Synergies of sugar-derived epoxy-silica hybrids and amino-functionalized silica NPs for advanced stone conservation

Innovative approaches to stone conservation materials are essential for addressing the challenges of preserving cultural heritage while meeting environmental and sustainability standards. Based on this premise, this study delves into the synergy between sol-gel processes and nanotechnology to develop advanced epoxy-silica hybrid materials tailored for stone conservation. This investigation specifically targeted the use of amino-functionalized mesoporous silica nanoparticles (NH2-SiO2 NPs) as interactive carriers for natural phenolic biocidal compounds within advanced sugar-based hybrid, demonstrating significant potential in the field of stone conservation. The novel products exhibited improved multifunctional properties attributed to the surface-modified NPs, which facilitated their intimate incorporation into the hybrid network. This integration promoted the creation of homogeneous materials with adapted flexibility, particularly critical for thermal expansion effects, and ensuring mechanical integrity even in outdoor environments. Furthermore, the encapsulation of natural biocidal compounds such as carvacrol and curcumin addressed their intrinsic drawbacks of volatility and coloration effects, preserving their efficacy while minimizing also plasticizing adverse effect on base thermoset. Indeed, the inclusion of curcumin-loaded NH2-SiO2 as dual bactericidal system provided the most favorable compatibility in terms of thermo-mechanical behavior. This system exhibited thermal resistance up to 350 °C and featured inter-joined flexible crystalline domains, distinguished by glass-transition temperatures of 67 and 99 °C. Furthermore, it exhibited enhanced hydrophobic properties reaching contact angles of 105°, and showcased an optimal live/dead ratio response against bacteria. The laboratory scale testing demonstrated a balanced set of features with significant capabilities in both recovering and maintaining the integrity of the lithic substrate, against common degradation patterns induced by prolonged acid exposure.

Contrastive Machine Learning with Gamma Spectroscopy Data Augmentations for Detecting Shielded Radiological Material Transfers

Data analysis techniques can be powerful tools for rapidly analyzing data and extracting information that can be used in a latent space for categorizing observations between classes of data. Machine learning models that exploit learned data relationships can address a variety of nuclear nonproliferation challenges like the detection and tracking of shielded radiological material transfers. The high resource cost of manually labeling radiation spectra is a hindrance to the rapid analysis of data collected from persistent monitoring and to the adoption of supervised machine learning methods that require large volumes of curated training data. Instead, contrastive self-supervised learning on unlabeled spectra can enhance models that are built on limited labeled radiation datasets. This work demonstrates that contrastive machine learning is an effective technique for leveraging unlabeled data in detecting and characterizing nuclear material transfers demonstrated on radiation measurements collected at an Oak Ridge National Laboratory testbed, where sodium iodide detectors measure gamma radiation emitted by material transfers between the High Flux Isotope Reactor and the Radiochemical Engineering Development Center. Label-invariant data augmentations tailored for gamma radiation detection physics are used on unlabeled spectra to contrastively train an encoder, learning a complex, embedded state space with self-supervision. A linear classifier is then trained on a limited set of labeled data to distinguish transfer spectra between byproducts and tracked nuclear material using representations from the contrastively trained encoder. The optimized hyperparameter model achieves a balanced accuracy score of 80.30%. Any given model—that is, a trained encoder and classifier—shows preferential treatment for specific subclasses of transfer types. Regardless of the classifier complexity, a supervised classifier using contrastively trained representations achieves higher accuracy than using spectra when trained and tested on limited labeled data.

Effect of Tai Chi exercise on bone health and fall prevention in postmenopausal women: a meta-analysis

BackgroundThe bone status of postmenopausal women is worsening. In fact, postmenopausal period is the high incidence stage of osteoporosis and falls. Notably, a recent study has pointed out that exercise can improve bone health in postmenopausal women. However, the effect of Tai Chi exercise on postmenopausal women is controversial. Therefore, a meta-analysis was designed to analyze the effect of Tai Chi exercise on bone health and fall prevention in postmenopausal women.MethodsThe researches on Tai Chi improving the bone health of postmenopausal women before August 31, 2023 were collected from Chinese and English databases, such as PubMed, Embase, and Web of Science, etc. The risk of bias of the included studies was assessed using the Cochrane risk-of-bias tool for randomized trials. Besides, R software 4.3.1 was employed to analyze the effect sizes in the meta-analysis to summarize the impact of Tai Chi on vertebral bone mineral density, serum calcium, clinical balance scores, the number of falls, total falls, and health status scores in postmenopausal women.ResultsThere were 12 studies eventually included in this meta-analysis. A total of 1,272 postmenopausal women were involved, including 628 in the experimental group (intervention with Tai Chi exercise) and 644 in the control group (without any intervention). Briefly, postmenopausal women practicing Tai Chi presented a significant increase in vertebral bone density [standardized mean difference (SMD) = 0.37, 95% confidence interval (CI) (0.04–0.71), P = 0.03] and health status score [SMD = 0.25, 95% CI (0.01–0.49), P = 0.04]. In contrast, there were no significant differences for postmenopausal women between the two groups in terms of serum calcium [SMD = -0.01, 95% CI (-0.39, 0.36), P = 0.77], clinical balance [SMD = 0.17, 95% CI (-0.01, 0.46), P = 0.23], number of falls [SMD = -0.61, 95% CI (-1.24, 0.02), P = 0.06] and total falls [odds ratio = 0.35, 95% CI (0.11–1.12), P = 0.07].ConclusionTai Chi exercise can improve the bone mineral density of postmenopausal women, thereby maintaining bone health. Hence, Tai Chi exercise is necessary to prevent osteoporosis.

Fractional Diversity Entropy: A Vibration Signal Measure to Assist a Diffusion Model in the Fault Diagnosis of Automotive Machines

Real-world vibration signal acquisition of automotive machines often results in imbalanced sample sets due to restricted test conditions, adversely impacting fault diagnostic accuracy. To address this problem, we propose fractional diversity entropy (FrDivEn) and incorporate it into the classifier-guided diffusion model (CGDM) to synthesize high-quality samples. Additionally, we present a corresponding imbalanced fault diagnostic method. This method first converts vibration data to Gramian angular field (GAF) image samples through GAF transformation. Then, FrDivEn is mapped to the gradient scale of CGDM to trade off the diversity and fidelity of synthetic samples. These synthetic samples are mixed with real samples to obtain a balanced sample set, which is fed to the fine-tuned pretrained ConvNeXt for fault diagnosis. Various sample synthesizers and fault classifiers were combined to conduct imbalanced fault diagnosis experiments across bearing, gearbox, and rotor datasets. The results indicate that for the three datasets, the diagnostic accuracies of the proposed CGDM using FrDivEn at an imbalance ratio of 40:1 are 91.22%, 87.90%, and 98.89%, respectively, which are 7.32%, 11.59%, and 3.48% higher than that of the Wasserstein generative adversarial network (WGAN), respectively. The experimental results across the three datasets validated the validity and generalizability of the proposed diagnostic method.

Innovation capability as a survival strategy for MSMEs during the economic recovery from the COVID-19 pandemic

This study aims to analyze the effect of organizational learning on organizational performance and innovation ability’s moderating variables on the effect of organizational learning on organizational performance. A quantitative approach is used that focuses on hypothesis testing and measurable data and produces generalizable conclusions. The analysis technique used is structural equation modeling (SEM). The contribution of this research is unique because it gives a more specific balanced score card design for micro, small and medium enterprise (MSME) performance to capture dimensions not revealed in existing studies. The results of this study show that organizational learning (exploitation, exploration and ambidexterity) has a positive effect on innovation capability, and vice versa. The theoretical implication of this research is that it offers a broad perspective on how MSMEs function in a pandemic and the tactics they use to overcome adversity and become resilient. Organizational learning and innovation are the two variable components in this study and are utilized as the main drivers of small and medium-sized enterprise (SME) performance. This research has implications for entrepreneurs, as SMEs can apply the findings to enhance their business performance.

Medium-voltage feeder blocks division method considering source-load uncertainty and characteristics complementary clustering

Existing feeder block division methods fail to consider the complementary characteristics and uncertainty between power sources and loads, which result in excessive feeder blocks, low inter-block balance, and significant disparity in net load peak-valley difference. To address these issues, a medium-voltage feeder block division method that considers the uncertainty and complementary characteristics of sources and loads is proposed. Firstly, based on the probability density characteristics of sources and loads, an uncertainty model of DG output and load demand is established. Secondly, considering the constraints of block maximum load rate and feeder non-crossing, a feeder block division model is established. Additionally, a set of center circles is defined, and based on this, an improved K-means clustering algorithm is proposed. The initial clustering centers based on the center circles is set, and the clustering centers based on the arcs of the center circles corrected. And the weighted distances between power sources and clustering centers are calculated. An algorithm flow for improved K-means clustering feeder block division is designed accordingly. Finally, the case studies show that the result of block division is improved.

Deep learning ensemble approach with explainable AI for lung and colon cancer classification using advanced hyperparameter tuning

Lung and colon cancers are leading contributors to cancer-related fatalities globally, distinguished by unique histopathological traits discernible through medical imaging. Effective classification of these cancers is critical for accurate diagnosis and treatment. This study addresses critical challenges in the diagnostic imaging of lung and colon cancers, which are among the leading causes of cancer-related deaths worldwide. Recognizing the limitations of existing diagnostic methods, which often suffer from overfitting and poor generalizability, our research introduces a novel deep learning framework that synergistically combines the Xception and MobileNet architectures. This innovative ensemble model aims to enhance feature extraction, improve model robustness, and reduce overfitting.Our methodology involves training the hybrid model on a comprehensive dataset of histopathological images, followed by validation against a balanced test set. The results demonstrate an impressive classification accuracy of 99.44%, with perfect precision and recall in identifying certain cancerous and non-cancerous tissues, marking a significant improvement over traditional approach.The practical implications of these findings are profound. By integrating Gradient-weighted Class Activation Mapping (Grad-CAM), the model offers enhanced interpretability, allowing clinicians to visualize the diagnostic reasoning process. This transparency is vital for clinical acceptance and enables more personalized, accurate treatment planning. Our study not only pushes the boundaries of medical imaging technology but also sets the stage for future research aimed at expanding these techniques to other types of cancer diagnostics.

Relationship between playing-related factors and occupational balance in professional violinists.

Playing performance of musicians may affect their occupational balance. The violin is one of the riskiest string instruments for the musculoskeletal health. To show the effect of socio-demographics, playing posture, pain, and functionality on occupational balance in professional violinists in Istanbul. Forty-five violinists aged 29.1±10.6 years were included. The Personal Information Form, the Edinburgh Handedness Inventory, the Wong-Baker Faces Pain Rating Scale, the Disability of Arm, Shoulder and Hand - Sports/Musicians (DASH-SM), the Rapid Upper Limb Assessment, and the 11-item revised version of the Occupational Balance Questionnaire (OBQ11 - T) were used. Spearman correlation analysis was performed to examine the relationship between the variables and occupational balance. The only significant correlation was found between doing regular exercise and occupational balance (r = 0.539, p < 0.001) with those having an exercise habit reporting higher occupational balance scores. The mean pain score of the violinists increased from a pre-performing mean of 1.6±2.3 to a post-performance mean of 3.91±2.4. Musicians indicate that they practice physical exercise regularly. A strong methodological limitation of this study is that variables like exercise were evaluated with a self-reported survey which limited the analysis and so we hardly find any relationships between them. To the best of our knowledge, this is the first study to evaluate the relationship between playing-related factors and occupational balance in violinists. There may be other factors affecting occupational balance in violinists and also in the other musicians. Similar studies are needed in other countries also using different assessments specific to musicians.

Association between the oxidative balance score and estimated pulse wave velocity from the National Health and Nutrition Examination Survey (2005–2018)

BackgroundNo research report has been conducted to investigate the impact of oxidation balance score (OBS) on the estimated pulse wave velocity(ePWV).We aimed to examine the association between OBS and ePWV.MethodWe evaluated data for 13,073 patients from the National Health and Nutrition Examination Survey (NHANES). The exposure variable was OBS. The outcome variables was combination of ePWV and arterial stiffness.ResultsWe observed a significant negative correlation between OBS (Per 1SD increase) and ePWV in the gradually adjusted models. Based on the aforementioned results, a two-piecewise logistic regression adjusted model was subsequently employed to establish the association between OBS and elevated ePWV, and the inflection point was determined as 5. The increased risk of elevated ePWV (OR:0.70; 95%CI:0.51–0.94) gradually decreases with the increase of OBS on the left side of the inflection point; however, when OBS exceeds 5, this decrease in risk of elevated ePWV(OR:1.00; 95%CI:0.96–1.04) is no longer observed (P for log likelihood ratio test = 0.028).ConclusionsThere exists a significant association between OBS and ePWV in the context of American adults. Specifically, OBS exhibits a negative correlation with ePWV; however, when considering an elevated ePWV, a saturation effect is observed in relation to OBS.

Resection versus resection with ablation: Analysis from the colorectal liver operative metastasis international collaborative.

Thermal ablation has recently become a key therapy for the treatment of colorectal liver metastasis (CLM). However, the role of ablation in combination with resection has not yet been firmly established. We hypothesize that in patients with CLM, those who undergo liver resection with ablation (RA) have similar outcomes compared with those who undergo liver resection only. We reviewed a multicenter international database of 906 surgical procedures for CLM from 5 high volume hepatobiliary surgical units. Patients undergoing RA (n = 63) were matched based on the number of lesions and tumor size using a 1:1 balanced propensity score analysis with those having resection only (n = 63). Our primary outcomes were overall survival (OS) and disease-free survival (DFS). The mean age of our cohort was 58 ± 11 years, with 43% females. With a median follow-up of 70.8 months, patients in the resection and RA group had a median OS of 45.1 and 54.8 months (p = 0.71), respectively. The median DFS was 22.7 and 14.2 months (p = 0.045), respectively. Using a multivariate Cox proportional hazards regression model, the treatment approach was not associated with OS (p = 0.94) or DFS (p = 0.059). A higher number of lesions is independently associated with worse DFS (hazard ratio: 1.12, p < 0.01). When there was disease recurrence, the region of recurrence was similar between the RA versus resection only groups (p = 0.27), but there was a shorter time to recurrence in the RA group (p = 0.002). For CLM, the treatment approach was not significantly associated with OS or DFS, while tumor biology likely played an important role. Prospective research on the quality and effectiveness of thermal ablation combined with hepatic resection is warranted.

The Impact of an Educational Program on the Stages of Change for Mammography Screening Among Rural Women with Low Health Literacy

Background: The aim of the study was to investigate the effect of an educational program on the mammography screening stage of change among rural women with low health literacy. Methods: In general, 52 rural women participated in this experimental study. The samples were selected using a multi-stage cluster sampling method and divided into two intervention (n=26) and control (n=26) groups. An educational program was implemented for the intervention group for one month. The data collection tool was a valid questionnaire based on constructs of the transtheoretical model (TTM) related to mammography screening, which was completed in the pre-test phase and after three and six months. The data were analyzed using SPSS 16 at the significant level of 0.05. Results: There was no significant difference between the control and intervention groups at the pre-test phase (P&gt;0.05). The intervention group demonstrated considerable progress in the stage of change for mammography screening after three- and six-month follow-ups (P&lt;0.001, odds ratio [OR]=2.54). The odds ratio of progress in the stages of change in the intervention group compared to the control group significantly increased after three (P&lt;0.001, OR=4.29) and six (P&lt;0.001, OR=5.45) months of follow-up. In addition, the findings indicated a significant increase in the mean scores of decisional balance, processes of change, and self-efficacy in the intervention group compared to the control group three and six months after the educational intervention (P&lt;0.005). Conclusion: The educational program significantly advanced mammography screening stages among rural women with low health literacy. These results highlight the program’s effectiveness in enhancing screening behaviors in this underserved population.

The Use of Telerehabilitation to Improve Movement-Related Outcomes and Quality of Life for Individuals With Parkinson Disease: Pilot Randomized Controlled Trial.

Individuals with Parkinson disease (PD) can improve their overall mobility and participation in daily activities as they engage in frequent exercise. Despite the need for individually tailored exercises, persons with PD often face barriers to accessing physical rehabilitation professionals who can provide them. Telerehabilitation (TR) may facilitate access to necessary and individually tailored rehabilitation for individuals with PD. The purpose of this study was to assess the feasibility of TR for individuals with PD and explore clinical outcomes compared to in-person care. This was a pilot randomized controlled trial conducted at 2 outpatient neurorehabilitation clinics with 3 study groups: clinic+TR, TR-only, and usual care (UC). TR was administered using a web-based application with a mobile app option. One-hour interventions were performed weekly for 4 weeks, in-person for the clinic+TR and UC groups and virtually for the TR-only group. Home exercises were provided on paper for the UC group and via the web-based platform for the clinic+TR and TR-only groups. Feasibility was assessed by recruitment and retention success and patient and therapist satisfaction, as rated in surveys. Clinical outcomes were explored using performance and patient-reported measures in between- and within-group analyses. Of 389 patients screened, 68 (17.5%) met eligibility criteria, and 20 (29.4% of those eligible) were enrolled (clinic+TR, n=6; TR-only, n=6; and UC, n=8). One patient (TR-only) was withdrawn due to a non-study-related injurious fall. Regardless of group allocation, both patients and therapists generally rated the mode of care delivery as "good" or "very good" across all constructs assessed, including overall satisfaction and safety. In the analysis of all groups, there were no differences in clinical outcomes at the discharge visit. Within-group differences (from baseline to discharge) were also generally not significant except in the UC group (faster 5-time sit-to-stand time and higher mini balance evaluation systems test balance score) and clinic+TR group (higher mini balance evaluation systems test balance score). High satisfaction amongst patients and clinicians regardless of group, combined with nonsignificant between-group differences in clinical outcomes, suggest that TR is feasible for individuals with PD in early-moderate stages. Future trials with a larger sample are necessary to test clinical effectiveness. As larger trials enroll patients with diverse characteristics (eg, in terms of age, disease progression, caregiver support, technology access and capacity, etc), they could begin to identify opportunities for matching patients to the optimal utilization of TR as part of the therapy episode. ClinicalTrials.gov NCT06246747; https://clinicaltrials.gov/study/NCT06246747.

Association between oxidative balance score and diabetic kidney disease, low estimated glomerular filtration rate and albuminuria in type 2 diabetes mellitus patients: a cross-sectional study.

The oxidative balance score (OBS) is a comprehensive concept that includes 20 oxidative stressors and can be used to assess individual pro-oxidant versus antioxidant exposure, and the aim of the present study was to investigate the association between OBS and the risk of diabetic kidney disease (DKD), low estimated glomerular filtration rate (low-eGFR) and albuminuria in patients with diabetes mellitus (DM). This cross-sectional study included nationally representative consecutive National Health and Nutrition Examination Survey DM patients aged 18 years and older from 2003-2018. The continuous variable OBS was converted into categorical variables by quartiles, and weighted multiple logistic regression analyses and restricted triple spline models were used to explore the relationships. We also performed subgroup analyses and interaction tests to verify the stability of the results. A total of 5389 participants were included, representing 23.6 million non-institutionalized US residents. The results from both multivariate logistic regression analysis and restricted cubic spline models indicated that OBS and dietary OBS levels were negatively associated with the risk of DKD, low-eGFR, and albuminuria, without finding a significant correlation between lifestyle OBS and these clinical outcomes. Compared to the lowest OBS quartile group, the prevalence risk of DKD (OR = 0.61, 95% CI: 0.46-0.80), low-eGFR (OR = 0.46, 95% CI: 0.33-0.64) and albuminuria (OR = 0.68, 95% CI: 0.51-0.92) decreased by 39%, 54% and 32%, respectively, in the highest OBS quartile group. The results remained stable in subgroup analyses and no interaction between subgroups was found. Higher levels of OBS and dietary OBS were associated with a lower risk of DKD, low-eGFR, and albuminuria. These findings provided preliminary evidence for the importance of adhering to an antioxidant-rich diet and lifestyle among individuals with diabetes.

Enhancing Music Mood Recognition with LLMs and Audio Signal Processing: A Multimodal Approach

Abstract: Music Mood Recognition aims to allow computers to understand the emotions behind music the way humans do, in order to facilitate better perception of media by computers to aid in enhanced services like music recommendations, therapeutic interventions, and Human Computer Interaction. In this paper, we propose a novel approach to improving Music Mood Recognition using a multi-modal model that uses lyrical and audio features of a song. Lyrical features are analysed using stateof-the-art open-source Large Language Models like Microsoft Phi-3 to classify lyrics from one of the four possible emotion categories as per the James Russel Circumplex Model. Audio features are used to train a Deep Learning (ConvNet) model to predict emotion classes. A multimodal combiner model with Audio and Lyrics is then trained and deployed to enable accurate predictions. The dataset used in this research is “MoodyLyrics”, a collection of 2000+ songs classified with one of 4 possible emotion classes as per the James Russel Circumplex Model. Due to compute limitations, we are using a balanced set of 1000 songs to train and test our models. The workin this paper outperforms most other multimodal researches by allowing higher accuracies with universal language support

Older adult women with chronic anorexia nervosa: heterogeneous adaptation to undernutrition over time.

Anorexia nervosa (AN) in older adult women is primarily described through reviews or case reports focusing on psychiatric traits, with no comprehensive studies evaluating their complete nutritional and hormonal profiles. This study aimed to describe a group of women with anorexia nervosa aged above 35 years old (AN35), and compare them with young women with anorexia nervosa (ANY) and normal-weight control participants. Anthropometric, metabolic, nutritional, and psychiatric parameters were collected and compared among three groups of women: 50 AN35, 37 ANY, and 38 controls. AN35 exhibited a mean disease duration of 271 ± 19 months, with 94% chronic forms and 58% restrictive types. Despite having similar BMI as ANY, AN35 displayed more altered parameters, including higher liver enzymes (p = 0.007), free T3 (p = 0.0046) and leptin (p < 0.0001); and lower albumin (p = 0.0029), and white cells (p < 0.0001). AN35 showed significant heterogeneity in hormonal adaptation, such as free T3. Half of the patients aged above 51 years revealed high gonadotropin levels despite being undernourished. Additionally, AN35 groups presented with 50% of bones fractures, decreased T-scores under -2.5 (p < 0.0001 for femoral), and altered micro architectural HRPQT parameters compared to ANY. Anorexia nervosa in older adult women is predominantly chronic. Nutritional parameters changes with age suggests a significant heterogeneity and possible adaptation of energy balance and bodyweight set point for others. Complications may be severe, altering the quality of life, and sometimes potentially lethal. These findings highlight the potential adaptation of energy balance with age, and should assist clinicians in clinical practice.

Association between oxidative balance score and female infertility from the national health and nutrition examination survey 2013-2018.

The correlation between oxidative stress and female infertility pathogenesis was established, and the oxidative balance score (OBS) can serve as a measure of overall oxidative stress burden within an individual. Prior reports have not addressed the relationship between OBS and female infertility. This study endeavors to investigate the association between infertility risk in female and OBS. The analysis focused on data from the National Health and Nutrition Examination Survey 2013-2018. OBS was determined from 16 dietary components and 4 lifestyle components. Multivariate logistic regression was employed to investigate the relationship between OBS and female infertility. Further stratified analysis was conducted to examine the associations across various subgroups. To elucidate the dose-response relationship between infertility risk in female and OBS, a restricted cubic spline function was employed. The study included a total of 1410 participants. Through weighted multivariable logistic regression analysis, we observed a consistent inverse correlation between OBS and the risk of female infertility [OR (95% CI) = 0.97 (0.95, 0.99), p = 0.047]. When participants were segregated into quartiles based on OBS, those in the highest quartile had a 61% [OR (95% CI) = 0.39 (0.2, 0.79), p = 0.01] reduced risk of infertility compared to those in the lowest quartile of OBS. A trend test assessing OBS by quartile also revealed the relationship between OBS and female infertility. This correlation remained constant across both dietary and lifestyle OBS. Additionally, lifestyle OBS and female infertility exhibited a nonlinear association. A sensitivity analysis verified the consistency of our findings. The study found that a higher OBS is associated with a lower prevalence of female infertility. These results emphasized the potential role of oxidative homeostasis in the pathogenesis of infertility and highlighted the importance of follow-up studies and prevention strategies.

Balanced Quality Score: Measuring Popularity Debiasing in Recommendation

Popularity bias is the tendency of recommender systems to further suggest popular items while disregarding niche ones, hence giving no chance for items with low popularity to emerge. Although the literature is rich in debiasing techniques, it still lacks quality measures that effectively enable their analyses and comparisons. In this article, we first introduce a formal, data-driven, and parameter-free strategy for classifying items into low, medium, and high popularity categories. Then we introduce Balanced Quality Score (BQS) , a quality measure that rewards the debiasing techniques that successfully push a recommender system to suggest niche items, without losing points in its predictive capability in terms of global accuracy. We conduct tests of BQS on three distinct baseline collaborative filtering frameworks: one based on history-embedding and two on user/item-embedding modeling. These evaluations are performed on multiple benchmark datasets and against various state-of-the-art competitors, demonstrating the effectiveness of BQS.

Predicting Equity Crowdfunding Success

Equity crowdfunding has grown exponentially in the United States since the passage of the JOBS Act in 2013, yet it continues to be a research area that is relatively unexplored in the United States due to the limited availability of data. U.S equity crowdfunding campaigns are notoriously unsuccessful, and this paper develops a predictive model for equity crowdfunding success to determine whether the positivity of the language used, and the length of the campaign description influences an investor’s decision to invest. A model is developed on a balanced training set and applied to a test set, and the overall results are evaluated using a confusion matrix to determine the accuracy, precision, and recall of the model. Our overall results indicate that both the tone of sentiment and the length of the campaign description are predictive of an equity crowdfunding campaign’s success. Specifically, the potential investors appear to be attracted to positive campaign descriptions that are written with concise language.

Balance and strength measures are associated with incident dementia in older men

BackgroundAs people age the risk of dementia increases. Balance and strength deteriorate with ageing, but their associations with dementia are not clear. We aimed to determine relationships of balance and strength performance with incident dementia in the Health in Men Study (HIMS) cohort. MethodsWe used wave 4 of the HIMS as baseline for analyses (2011–2013), following 1261 men until December 2017 via data linkage to determine incident dementia. Balance was measured using a modified Balance Outcome Measure for Elder Rehabilitation (mBOOMER) Score and strength with the knee extension test. Cox proportional hazards regression was used, adjusting for sociodemographic and health data. Strength and balance scores were analysed non-linearly using restricted cubic splines. Results13.7% of men were diagnosed with dementia over a mean period of 4.7 (SD 1.5) years. Higher baseline mBOOMER scores were associated with a reduced risk of incident dementia, with greater changes in risk at higher mBOOMER scores (9 vs 8: HR 0.80, 95% CI 0.73–0.88; 12 vs 11: 0.49, 95% HR 0.36–0.68). Higher baseline lower limb strength was associated with a reduced risk of incident dementia, with greater changes occurring at lower scores, plateauing at around 25 kg (5 vs 4: HR 0.93, 95% CI 0.89–0.98; 25 vs 24: HR 0.99, 95% CI 0.95–1.03). ConclusionsThis study demonstrated a non-linear association of better performance in both strength and balance with reduced likelihood of incident dementia. These results raise the hypothesis that strategies to improve strength and balance could reduce the incidence of dementia in older men.

Across the professional lifespan: comparing the workforce trends of early career and established counselling psychologists in South Africa

ABSTRACT Counselling Psychologists (CPs) constitute a considerable proportion of psychologists in South Africa (SA), yet empirical knowledge on this workforce remains limited. Furthermore, changes within this workforce overtime have not been thoroughly examined. This study compares early career (<10 years) and established (>10 years) CPs relating to demographic characteristics, work settings, professional roles and activities, career satisfaction, and perspectives on efforts to demarcate the practice of CPs in SA. A total of 512 survey responses were analysed, with 39% representing early career CPs and 61% representing established CPs. Findings reveal significant differences between early career and established CPs across several domains, including age, race, geographic location, highest professional degree, languages spoken; current job-seeking status; satisfaction with income, employment opportunities, work-life balance and primary work settings; likelihood of emigration; and supervision frequency and format. Overall, the results suggest movement towards transformation within the CP profession in SA. Nevertheless, systemic issues continue to hinder the optimal utilisation and equitable distribution of CPs within the country. Advocacy and ongoing workforce analysis is thus essential to support, retain, and effectively utilise CPs as a valuable resource, especially in light of the ongoing debates surrounding the implementation of the National Health Insurance (NHI) system in SA.