Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison of Diagnostic Test Accuracy of Cone-Beam Breast Computed Tomography and Digital Breast Tomosynthesis for Breast Cancer: A Systematic Review and Meta-Analysis Approach

Background: Cone-beam breast computed tomography (CBBCT) and digital breast tomosynthesis (DBT) remain the main 3D modalities for X-ray breast imaging. This study aimed to systematically evaluate and meta-analyze the comparison of diagnostic accuracy of CBBCT and DBT to characterize breast cancers. Methods: Two independent reviewers identified screening on diagnostic studies from 1 January 2015 to 30 December 2021, with at least reported sensitivity and specificity for both CBBCT and DBT. A univariate pooled meta-analysis was performed using the random-effects model to estimate the sensitivity and specificity while other diagnostic parameters like the area under the ROC curve (AUC), positive likelihood ratio (LR+), and negative likelihood ratio (LR−) were estimated using the bivariate model. Results: The pooled sensitivity specificity, LR+ and LR− and AUC at 95% confidence interval are 86.7% (80.3–91.2), 87.0% (79.9–91.8), 6.28 (4.40–8.96), 0.17 (0.12–0.25) and 0.925 for the 17 included studies in DBT arm, respectively, while, 83.7% (54.6–95.7), 71.3% (47.5–87.2), 2.71 (1.39–5.29), 0.20 (0.04–1.05), and 0.831 are the pooled sensitivity specificity, LR+ and LR− and AUC for the five studies in the CBBCT arm, respectively. Conclusions: Our study demonstrates that DBT shows improved diagnostic performance over CBBCT regarding all estimated diagnostic parameters; with the statistical improvement in the AUC of DBT over CBBCT. The CBBCT might be a useful modality for breast cancer detection, thus we recommend more prospective studies on CBBCT application.
Parallel Learning-Based Steering Control for Autonomous Driving

Steering control for autonomous vehicles at high speeds is challenging due to the highly nonlinear vehicle dynamics. The traditional model-based controllers usually degrade significantly in this case. With the development of artificial intelligence, learning-based control methods are emerging as promising alternatives. These methods require a tremendous amount of training data to achieve acceptable performances. However, the data collection process is costly or inefficient. To solve this problem, we propose a parallel learning-based steering control method. Specifically, we first build a neural network (NN) based trajectory generative model (GeneratingNN) based on limited steering-trajectory raw data. The GeneratingNN can efficiently generate sufficient steering-trajectory data by enumerating the allowable steering actions sequences. Then, based on the raw data and generated data, we train another NN (RecallingNN) to learn the inverse mapping relationship between steering actions and trajectories. Hence, the RecallingNN can efficiently recall appropriate steering actions once given the previewed trajectory points. In addition, to further enhance the control accuracy and robustness, we use a simple feedback controller to handle the unmodeled dynamics and external disturbance. Testing results validate that the proposed method can achieve better tracking accuracy, stability and computational efficiency.
Long-Lasting Olfactory Dysfunction in Hospital Workers Due to COVID-19: Prevalence, Clinical Characteristics, and Most Affected Odorants

Hospital workers have increased exposure risk of healthcare-associated infections due to the frontline nature of their work. Olfactory dysfunction is highly prevalent. The objectives for this investigation are to study the prevalence of long-lasting olfactory dysfunction associated with COVID-19 infection in hospital workers during the first pandemic wave, to identify clinical characteristics and associated symptomatology, and to analyze how many patients with COVID-19 infection had developed olfactory dysfunction during infection and maintained a reduced olfactory function for approximately 10 weeks after diagnosis. Between June and July of 2020, a cross-sectional study was carried out at the Hospital Central de la Cruz Roja San José and Santa Adela in Madrid, Spain. One hundred sixty-four participants were included, of which 110 were patient-facing healthcare staff and 54 were non-patient-facing healthcare staff. Participants were split into three groups, according to COVID-19 diagnosis and presence of COVID-19 related olfactory symptomatology. Participants were asked to complete a structured online questionnaire along with Sniffin’ Stick Olfactory Test measurements. In this study, 88 participants were confirmed for COVID-19 infection, 59 of those participants also reported olfactory symptomatology. The prevalence of COVID-19 infection was 11.35%, and the prevalence for olfactory dysfunction was 67.05%. Olfactory dysfunction associated with COVID-19 infection leads to long-lasting olfactory loss. Objective assessment with Sniffin’ Stick Olfactory Test points to odor identification as the most affected process. Lemon, liquorice, solvent, and rose are the odors that are worst recognized. Mint, banana, solvent, garlic, coffee, and pineapple, although they are identified, are perceived with less intensity. The findings of this study confirmed a high prevalence of SARS-CoV-2 infection among the hospital workers.
Decellularised Cartilage ECM Culture Coatings Drive Rapid and Robust Chondrogenic Differentiation of Human Periosteal Cells

The control of cell behaviour in an effort to create highly homogeneous cultures is becoming an area of intense research, both to elucidate fundamental biology and for regenerative applications. The extracellular matrix (ECM) controls many cellular processes in vivo, and as such is a rich source of cues that may be translated in vitro. Herein, we describe the creation of cell culture coatings from porcine decellularised hyaline cartilage through enzymatic digestion. Surprisingly, heat-mediated sterilisation created a coating with the capacity to rapidly and robustly induce chondrogenic differentiation of human periosteal cells. This differentiation was validated through the alteration of cell phenotype from a fibroblastic to a cuboidal/cobblestone chondrocyte-like appearance. Moreover, chondrogenic gene expression further supported this observation, where cells cultured on heat sterilised ECM-coated plastic displayed higher expression of COL2A1, ACAN and PRG4 (p < 0.05) compared to non-coated plastic cultures. Interestingly, COL2A1 and ACAN expression in this context were sensitive to initial cell density; however, SOX9 expression appeared to be mainly driven by the coating independent of seeding density. The creation of a highly chondrogenic coating may provide a cost-effective solution for the differentiation and/or expansion of human chondrocytes aimed towards cartilage repair strategies.
Lenalidomide Improves Cognitive Function and Reduces Immune Reconstitution Inflammatory Syndrome in HIV-1-Related Cryptococcal Meningitis

Abstract Cryptococcal meningitis (CM) is a common opportunistic infection in patients with acquired immune deficiency syndrome. Although there is a standardized treatment for CM, some patients still have CM-associated immune reconstitution inflammatory syndrome (IRIS) after anti-cryptococcal and antiretroviral therapy, which manifests as cognitive impairment. We report two cases of CM-associated IRIS in human immunodeficiency virus (HIV) patients that were treated with lenalidomide. The treatment yielded a rapid clinical remission and improved cognitive function in both patients; their Montreal Cognitive Assessment (MoCA) and International HIV Dementia Scale (IHDS) scores improved. Furthermore, we evaluated changes in 32 cytokines in the cerebrospinal fluid of two patients and found that both MoCA and IHDS were significantly negatively correlated with inflammation-related factors (growth-related oncogene, interleukin [IL]-10, IL-2, IL-8, macrophage inflammatory protein-1β, tumor necrosis factor [TNF]-α) and significantly positively correlated with dementia-related factors (αβ42 and total tau). Our study reveals the potential of lenalidomide in treating cognitive impairment caused by immune-mediated inflammation in patients with HIV-CM. Moreover, we speculate that lenalidomide improves cognitive function by regulating intracranial inflammation via multiple pathways, not only by TNF-α blocking.
Automating Surgical Peg Transfer: Calibration With Deep Learning Can Exceed Speed, Accuracy, and Consistency of Humans

Peg transfer is a well-known surgical training task in the Fundamentals of Laparoscopic Surgery (FLS). While human surgeons teleoperate robots such as the da Vinci to perform this task with high speed and accuracy, it is challenging to automate. This paper presents a novel system and control method using a da Vinci Research Kit (dVRK) surgical robot and a Zivid depth sensor, and a human subjects study comparing performance on three variants of the peg-transfer task: unilateral, bilateral without handovers, and bilateral with handovers. The system combines 3D printing, depth sensing, and deep learning for calibration with a new analytic inverse kinematics model and time-minimized motion controller. In a controlled study of 3384 peg transfer trials performed by the system, an expert surgical resident, and 9 volunteers, results suggest that the system achieves accuracy on par with the experienced surgical resident and is significantly faster and more consistent than the surgical resident and volunteers. The system also exhibits the highest consistency and lowest collision rate. To our knowledge, this is the first autonomous system to achieve “superhuman” performance on a standardized surgical task. All data is available at https://sites.google. com/view/surgicalpegtransfer Note to Practitioners—This paper presents a new approach to calibrating cable-driven robots based on a combination of 3D printing, depth sensing, inverse kinematics, convex optimization, and deep learning. The approach is applied to calibrating the da Vinci, commercial surgical-assist robot, to automate a standard “pick and place” task. Experiments suggest that the resulting system matches human surgical expert performance in speed and accuracy and significantly outperforms humans in terms of consistency. All details on the system including CAD models, code, and user study data are available online.
BLENDED LEARNING IN ESL/EFL CLASS

Blended learning requires digital technology transformation for lecturers and students, up-to-date teaching methods, flexible learning processes, the effectiveness of time, space, budget, learning motivation, learning autonomy, all of which contribute to improving student learning achievement. However, current empirical research results do not support the claim that blended learning improves students' English proficiency and learning autonomy. Evidence shows that the blended learning has an effect on students' English competence, learning autonomy, motivation, and ICT literacy. For this article, the effect of blended learning in ESL/EFL was investigated and defined. This study is a quantitative explanatory research type with a pre-test and post-test design. The research participants were 198 students from the Department of Primary School Teacher Education, Universitas Katolik Indonesia Santu Paulus Ruteng. Seventy-four participants were chosen as samples using a random sampling method. Data was taken by test and non-test, and data was then analysed by a software program called SPSS 22.0. Twelve blended learning sessions, including six sessions in face-to-face settings and six sessions, are done virtually through the Zoom application. The results show that blended learning strengthens English student competence (the mean score on the post-test = 82.57), learning autonomy (88.57%), learning motivation (80%), and ICT literacy (71.43%).
A Real-Time Sensing System for Monitoring Neural Network Degeneration in an Alzheimer’s Disease-on-a-Chip Model

Stem cell-based in vitro models may provide potential therapeutic strategies and allow drug screening for neurodegenerative diseases, including Alzheimer’s disease (AD). Herein, we develop a neural stem cell (NSC) spheroid-based biochip that is characterized by a brain-like structure, well-defined neural differentiation, and neural network formation, representing a brain-on-a-chip. This system consisted of microelectrode arrays with a multichannel platform and allowed the real-time monitoring of network formation and degeneration by impedance analysis. The parameters of this platform for the real-time tracking of network development and organization were established based on our previous study. Subsequently, β-amyloid (Aβ) was added into the brain-on-a-chip system to generate an AD-on-a-chip model, and toxic effects on neurons and the degeneration of synapses were observed. The AD-on-a-chip model may help us to investigate the neurotoxicity of Aβ on neurons and neural networks in real time. Aβ causes neural damage and accumulates around neurites or inside neurospheroids, as observed by immunostaining and scanning electron microscopy (SEM). After incubation with Aβ, reactive oxygen species (ROS) increased, synapse function decreased, and the neurotransmitter-acetylcholine (ACh) concentration decreased were observed. Most importantly, the real-time analysis system monitored the impedance value variation in the system with Aβ incubation, providing consecutive network disconnection data that are consistent with biological data. This platform provides simple, real-time, and convenient sensing to monitor the network microenvironment. The proposed AD-on-a-chip model enhances the understanding of neurological pathology, and the development of this model provides an alternative for the study of drug discovery and cell–protein interactions in the brain.
Inferring Aquitard Hydraulic Conductivity Using Transient Temperature‐Depth Profiles Impacted by Ground Surface Warming

Aquitard hydraulic properties are notoriously difficult to assess, yet accurate aquitard hydraulic conductivity estimates are critical to quantify recharge and discharge to and from semi‐confined aquifer systems via hydraulic head gradients. Such flux quantification is required to evaluate the risks of aquifer exploitation by groundwater abstraction and aquifer vulnerability to surface contamination. In this study, we consider a regionally important aquitard and compare existing hydraulic conductivity estimates obtained through traditional methods to those inferred from long‐term hydraulic head monitoring and thermally derived vertical groundwater fluxes (0.04–0.25 m/y). We estimate the fluxes using numerical modeling to analyze the propagation of decadal climate signals into temperature‐depth profiles and fitting the simulated and observed inflection point depths (location of minimum temperature). Results suggest that climate‐disturbed temperature‐depth profiles paired with multi‐level head data can yield accurate vertical fluxes and aquitard hydraulic conductivities. This approach for characterizing groundwater systems and quantifying flows to and from sedimentary aquifers is more efficient but yields results that are comparable to conventional methods.
Knowledge and practice of rotary instrumentation in primary teeth among indian dentists: A questionnaire survey

Introduction: Use of rotary instrumentation for pulpectomy is a recent emerging concept in the field of pedodontics. The objective of this study was to evaluate the knowledge and practice of NiTi rotary instruments' usage in primary teeth by the Indian dentists. Materials and Methods: A self-administrated questionnaire was prepared and pretested and was given to the private practitioners. A total of 100 completed questionnaires were obtained. The data were entered and analyzed for frequency and percentages using Statistical Package for the Social Sciences (SPSS) software version 17. Results: In the present study, about 50% of the practitioners used rotary instrumentation of root canals in primary teeth, of which majority were postgraduates. ProTaper was the commonly used rotary system in primary teeth. The practitioners felt both taper and length of the existing rotary file to be the limitation for its use in primary teeth. Conclusion: From the present study, it is concluded that there is a need for comprehensive education programs to be conducted to increase the awareness and use of rotary files for pulpectomy in primary teeth. In addition, there is a need for an exclusive pediatric rotary system for convenience in using it in children.
The Role of Digital Leadership, Customer Orientation and Business Model Innovation for IoT Companies

Internet of Things (IoT) is an emerging and promising technology but complex and technologically is in uncertain environment. In order to develop the effective solution and maintain the competitive advantages, companies have to innovate the business model continuously. Business Model Innovation for IoT companies requires to drive the company performance. Despite the need of IoT companies to renew their business model to effectively create value for customers and capture value for the company, the significant factors of business model innovation for IoT companies have remained underresearch so far. This study addresses this knowledge gap by exploring the significant factors of business model innovation and ultimate impact towards IoT company performance. This study uses the PLS-SEM method involving samples of 75 IoT companies in Indonesia as developing countries who are still in a nascent stage of digitalization. Digital Leadership, Customer Orientation have been identified as significant factors of business model innovation while IoT company performance as the main expected outcomes.
From School Halls to Shopping Malls: Multilevel Predictors of Police Contact In and Out of School

Objectives: Individual- and school-level factors associated with youth being stopped, searched, or arrested in school are identified. Correlates of community-based contact are also examined. Methods: Longitudinal student surveys and corresponding school-level data come from 21 middle and high schools in 6 districts in St. Louis County, Missouri. Multilevel multinomial logistic regression was used to assess factors related to a three-category dependent variable, distinguishing youth with: (1) no police contact, (2) in-school contact, and (3) out-of-school contact. Independent variables capture student-level demographics, behavior, experiences, and perceptions and school-level characteristics and practices. Results: Factors associated with in-school contact include substance use, peer associations, prior contact, and prior school sanctions. Odds of school-based contact also increase when youth are less aware of school rules and perceive greater disorder. Among school-level characteristics, only officers responding to school problems is significantly associated with in-school contact. Conclusions: There is some consistency in individual-level factors associated with police contact across locations, particularly related to prior sanctions, but findings highlight potential mechanisms that vary across contexts. This study also provides evidence that some schoolwide responses may contribute to youth's likelihood of having police contact in school, but solutions should consider the fluidity of contact in schools and communities.
Genome-Wide Investigation of the PtrCHLP Family Reveals That PtrCHLP3 Actively Mediates Poplar Growth and Development by Regulating Photosynthesis

Chlorophyll (Chl) plays a crucial role in plant photosynthesis. The geranylgeraniol reductase gene (CHLP) participates in the terminal hydrogenation of chlorophyll biosynthesis. Although there are many studies related to the genome-wide analysis of Populus trichocarpa, little research has been conducted on CHLP family genes, especially those concerning growth and photosynthesis. In this study, three CHLP genes were identified in Populus. The evolutionary tree indicated that the CHLP family genes were divided into six groups. Moreover, one pair of genes was derived from segmental duplications in Populus. Many elements related to growth were detected by cis-acting element analysis of the promoters of diverse PtrCHLPs. Furthermore, PtrCHLPs exhibit different tissue expression patterns. In addition, PtrCHLP3 is preferentially expressed in the leaves and plays an important role in regulating chlorophyll biosynthesis. Silencing of PtrCHLP3 in poplar resulted in a decrease in chlorophyll synthesis in plants, thus blocking electron transport during photosynthesis. Furthermore, inhibition of PtrCHLP3 expression in poplar can inhibit plant growth through the downregulation of photosynthesis. Ultimately, PtrCHLP3 formed a co-expression network with photosynthesis and chlorophyll biosynthesis-related genes, which synergistically affected the growth and photosynthesis of poplars. Thus, this study provides genetic resources for the improved breeding of fast-growing tree traits.
Incidence of Spinal Anesthesia Induced Severe Hypotension among the Pregnant Women Undergoing Cesarean Section at Muhima Hospital

BackgroundThe spinal induced severe hypotension is frequently reported during cesarean section; the literature counts 70% of severe hypotension following spinal anesthesia for cesarean section. This complication is thought to be serious and even fatal, when not well managed; however, in Rwanda, we have a limited data about that spinal induced life-threatening complication. ObjectivesTo determine the incidence and factors associated with spinal anesthesia induced severe hypotension during caesarian section at Muhima hospital.MethodologyThe study was cross-sectional, descriptive and analytical in design. The study population was the pregnant women scheduled for cesarean section, and a sample size of 108 was used. A self-developed questionnaire was used as data collection tool. ResultsForty percent of participants’ experienced spinal anesthesia induced severe hypotension; while preloading, left tilt position and infusion of ephedrine, were associated with lower incidence of severe hypotension.ConclusionThe incidence of spinal induced severe hypotension is high, however, preloading; left lateral position and co-infusion of ephedrine were found to protect the participants from spinal induced severe hypotension. Therefore, these techniques should be promoted. Rwanda J Med Health Sci 2022;5(1):62-70
Board characteristics and Bank Performance: Which factor is more important?

This study seeks to find the rank of corporate governance characteristics that affect bank performance. The artificial neural network is employed in the analysis instead of regression analysis. There are two dependent variables which are ROA and PER that represents the accounting performance and the market performance. Size of the board of directors, gender diversity of the board, and board independence are the corporate governance characteristics considered in this study. Board independence is the most important factor in determining both accounting performance and market performance. However, the size of the board of directors becomes the second-factor affecting a bank’s accounting performance and the last factor affecting the bank’s market performance, while gender diversity is the last factor for accounting performance and the second factor for market performance.