Rapid Traction Research Articles

A comparative study of a two-stage surgical approach combining coronectomy with microimplant anchorage traction for extraction of impacted mandibular third molars with different traction angles

Objective: To establish a two-stage surgical procedure of impacted mandibular third molars (IMTMs) extractions assisted by coronectomy and microimplant anchorage traction and to investigate the influencing factors of root movement and the effects of different traction angles on the clinical outcomes. Methods: Fifty-three IMTM in contact with inferior alveolar nerve (IAN) that underwent tooth extraction in the Peking University School of Stomatology from January 2022 to June 2023 were included, with coronectomy and microimplant anchorage implantation in the first stage of the surgery, root traction was achieved with orthodontic elastic and microimplant anchorages by about 600 g of force, when the IMTM root was detached from IAN, a second surgery was performed to extract the residual root. The basic information of patients and M3M, data on the microimplant anchorage implantation and traction, imaging measurements, and complications were recorded and analyzed. Results: The movement distance of the residual roots was (1.80±0.92) mm, and the duration of traction was (32.9±7.9) d. Multiple linear regression analysis showed that the residual root movement distance was significantly correlated with age, gender, number of roots, traction angle, and depth of the distal bone defect of the second molar (P<0.05). The smaller the traction angle, the more significant the movement of the residual roots (P=0.044). In one case (1.9%, 1/53), the patient experienced abnormal sensation in the lower lip 16 days after traction. Conclusions: The two-stage surgical method of combined coronectomy with rapid traction technique to extract the IMTM allows for rapid movement of the residual root and reduces the risk of IAN injury. The efficiency of root movement can be accelerated by appropriately reducing the traction angle during surgery. The traction effect can be predicted based on indicators such as age, gender, number of roots and depth of distal bone defects of second molar.

Hyperbolic Deep Learning in Computer Vision: A Survey

Deep representation learning is a ubiquitous part of modern computer vision. While Euclidean space has been the de facto standard manifold for learning visual representations, hyperbolic space has recently gained rapid traction for learning in computer vision. Specifically, hyperbolic learning has shown a strong potential to embed hierarchical structures, learn from limited samples, quantify uncertainty, add robustness, limit error severity, and more. In this paper, we provide a categorization and in-depth overview of current literature on hyperbolic learning for computer vision. We research both supervised and unsupervised literature and identify three main research themes in each direction. We outline how hyperbolic learning is performed in all themes and discuss the main research problems that benefit from current advances in hyperbolic learning for computer vision. Moreover, we provide a high-level intuition behind hyperbolic geometry and outline open research questions to further advance research in this direction.

Evaluation of the current situation and quality of neonatal hearing screening from hearing screening practitioners’ perspective: a cross-sectional study

Background In recent years, neonatal hearing screening (NHS) has gained rapid traction in both developed and developing nations. However, the efficacy of these efforts depends on comprehensive standardization across all screening facets. This study aimed to assess the status and quality of NHS by investigating the knowledge, attitudes, beliefs, and practices of hearing screening practitioners regarding NHS. Methods A cross-sectional survey was conducted, and an online questionnaire based on the knowledge-attitude/belief (A/B)-practice model was distributed to all NHS practitioners in Luzhou, western China. Valid questionnaires were examined and uniformly graded. Results A total of 63 valid questionnaires were collected. The practitioners were mainly female (96.83%), with nursing backgrounds (63.49%), and undergraduate degrees (66.67%). Most had ≤5 years of experience (74.60%) and had junior/intermediate titles (93.65%). The NHS within the Luzhou area started in 2006 with provincial institutions, expanding to 42 institutions by 2022. Statistically significant correlations were observed between the A/B score and the conducting years of each NHS institution (p < .05) as well as between the Knowledge (K) and Practice (P) scores (p < .01). No significant correlation was found between the K score, P score, A/B score, and working years of practitioners (p > .05), or in the total score of NHS institutions at different levels or in different counties by one-way ANOVA (p > .05). Conclusions It has been 17 years since the first medical institution in Luzhou launched NHS, and the overall performance of practitioners from different institutions has been consistent in terms of their knowledge, attitudes, or level of practice. However, there is room for further improvement in both the professional development of individuals and aspects related to work, such as health education and long-term follow-up.

Развитие организационной модели труда в современных условиях: тенденции и эффекты

The results of effective work organization improve safety and the workers’ quality of life, and increase productivity. Globalisation and digitalization are dramatically changing and meaningfully affecting the organization of work. However, there is currently a lack of research in terms of the foundation of the labor process and its organization – co-operative activity. The article analyses how co-operative activity has a significant impact on the evolution of work organization and the factors influencing its development in a digitized environment. The results show that with the introduction of digital mobile technologies, the work organization model goes beyond the traditional management concept based on rigid hierarchy and managerial control. The implementation of flexible models of labor organization is possible only on the basis of new methods of management and development of employees, particularly in the practice of platform employment, which is gaining rapid traction around the world. In the absence of these conditions, there are many fears about future work related to the features of industry 4.0, which is based on digital technologies.

Upscaling potential of BIPV for public housing typologies in Singapore

This paper assesses the upscaling potential of Building Integrated Photovoltaics (BIPV) in the public housing stock of Singapore. While the installation of rooftop PV is gaining rapid traction in the city-state, there are still only few existing projects with façade PV. Considering the large share of façade areas available, this paper aims to identify the most suitable building typology for BIPV integration. The research methodologies include a city-wide analysis of solar potentials, photogrammetry-based solar assessments of the four most common housing typologies, and a load-matching analysis of a typical contemporary apartment unit. Furthermore, we conduct a qualitative analysis through interviews with public and private stakeholders, to understand the drivers and barriers of BIPV in Singapore. Our results reveal districts with the the highest total electricity generation potential such as “Bedok”, or others with larger façade than roof PV-potential such as “Bukit Merah”, where buildings often feature eastwards-oriented façades with low window-to-wall ratio, making them ideal for electricity production in the morning hours. Due to higher cloud coverage in the afternoon, Westward-oriented façades have an overall lower potential. The load-matching analysis shows, however, that peak demand in the morning and evening can generally not be met by BIPV only. The analysis of building typologies reveals that geometrically simpler linear buildings built in the 70’s and 80’s have higher total PV generation potential due to larger roof areas and less obstructed façades. The contemporary point towers with irregular façade surfaces show a larger fraction of façade BIPV electricity generation per floor area, exceeding the share of electricity produced on rooftops. A customized BIPV system will be promising for these newer building typologies, supported by soft factors identified in the interviews.

The image as a site of transgression: the case of Beirut counter-visuality since October 2019

ABSTRACT On 17 October 2019 in Beirut, a Lebanese state bodyguard confronted by demonstrators opened fire when a female protestor hit him with a side kick. Another protestor recorded this moment on his mobile phone. A single frame of the video footage was remediated shortly after as a still image and gained rapid traction across social media platforms, as did the original video. The circulation of the content online inspired a group of artists to remediate the digital image themselves into a series of artistic works, adding in the process additional layers of meaning and interpretation to its original context. Taking the digital image of the side kick as a case study, this qualitative research examines how five young Lebanese artists use ‘cyberartivism’ to participate in the rising wave of political and social transformation. Based on empirical material that consists of a series of interviews with five Lebanese artists, this study aims to understand the role of digital images in their transition from forms of evidence to remediated sites of transgression in the context of the October 2019 Revolution in Lebanon. Its purpose is to explore the way camera witnessing, connective witnessing, and the creative modification of an image and its circulation on social media can foster a sense of solidarity and dissent by empowering and strengthening protestors’ voices, thus generating new forms of leadership and agency.

A survey on face presentation attack detection mechanisms: hitherto and future perspectives.

The advances in human face recognition (FR) systems have recorded sublime success for automatic and secured authentication in diverse domains. Although the traditional methods have been overshadowed by face recognition counterpart during this progress, computer vision gains rapid traction, and the modern accomplishments address problems with real-world complexity. However, security threats in FR-based systems are a growing concern that offers a new-fangled track to the research community. In particular, recent past has witnessed ample instances of spoofing attacks where imposter breaches security of the system with an artifact of human face to circumvent the sensor module. Therefore, presentation attack detection (PAD) capabilities are instilled in the system for discriminating genuine and fake traits and anticipation of their impact on the overall behavior of the FR-based systems. To scrutinize exhaustively the current state-of-the-art efforts, provide insights, and identify potential research directions on face PAD mechanisms, this systematic study presents a review of face anti-spoofing techniques that use computational approaches. The study includes advancements in face PAD mechanisms ranging from traditional hardware-based solutions to up-to-date handcrafted features or deep learning-based approaches. We also present an analytical overview of face artifacts, performance protocols, and benchmark face anti-spoofing datasets. In addition, we perform analysis of the twelve recent state-of-the-art (SOTA) face PAD techniques on a common platform using identical dataset (i.e., REPLAY-ATTACK) and performance protocols (i.e., HTER and ACA). Our overall analysis investigates that despite prevalent face PAD mechanisms demonstrate potential performance, there exist some crucial issues that requisite a futuristic attention. Our analysis put forward a number of open issues such as; limited generalization to unknown attacks, inadequacy of face datasets for DL-models, training models with new fakes, efficient DL-enabled face PAD with smaller datasets, and limited discrimination of handcrafted features. Furthermore, the COVID-19 pandemic is an additional challenge to the existing face-based recognition systems, and hence to the PAD methods. Our motive is to present a complete reference of studies in this field and orient researchers to promising directions.

Cautious optimism regarding the use of home-based neuromodulation to treat depression

Weak-intensity neuromodulation involves the use of targeted transcranial stimulation to treat neuropsychiatric disorders, including depression. This type of neuromodulation has more favourable tolerability profiles1,2 than higher intensity neuromodulation techniques, such as repetitive transcranial magnetic stimulation and electroconvulsive therapy. As weak-intensity neuromodulation is delivered by portable, battery-driven devices, it can potentially be administered to patients at home. Such home-based neuromodulation is likely to play an increasing role in the treatment of psychiatric disorders in the near future,3 and neuromodulation is gaining rapid traction as an effective tool in interventional psychiatry.

Toward Robust River Plastic Detection: Combining Lab and Field‐Based Hyperspectral Imagery

AbstractPlastic pollution in aquatic ecosystems has increased dramatically in the last five decades, with strong impacts on human and aquatic life. Recent studies endorse the need for innovative approaches to monitor the presence, abundance, and types of plastic in these ecosystems. One approach gaining rapid traction is the use of multi‐ and hyperspectral cameras. However, most experiments using this approach were in controlled environments, making findings challenging to apply in natural environments. We present a method linking lab‐ and field‐based identification of macroplastics using hyperspectral data (1,150–1,675 nm). Experiments using riverbank‐harvested macroplastics were set up in a laboratory environment, and on the banks of the Rhine River. Representative pixel selections of eleven lab‐based images (n = 786,264 pixels) and two field‐based images (n = 40,289 pixels) were used to analyze the differences between these environments. Next, classifier algorithms such as support vector machines (SVM), spectral angle mapper (SAM) and spectral information divergence (SID) were applied, because of their robustness to varying light conditions and high accuracies in mapping spectral similarities. Our results showed that SAM classifiers are most robust in separating plastic pixels from background elements. By applying lab‐based data for plastic detection in field‐based images, user accuracies for plastics to up to 93.6% (n = 8,370 plastic pixels) were attained. This study provides key fundamental insights in linking lab‐based data to plastic detection in the field. With this paper we aim to contribute to the development of future spectral missions to detect and monitor plastic pollution in aquatic ecosystems.

Can Digital Technologies Increase Consumer Acceptance of Circular Business Models? The Case of Second Hand Fashion

Experimentation with, and the implementation of, circular business models (CBMs) has gained rapid traction within the textiles and fashion industry over the last five years. Substitution of virgin materials with bioderived alternatives, extending the lifecycle of garments through resale, and rental services and the recycling or upcycling of garments are some of the strategies being used to reduce the 1.2 billion tonnes of greenhouse gas emissions and 92 million tonnes of waste associated with the sector in 2017. However, whilst CBMs demonstrate environmental and economic benefits, low consumer acceptance is considered by business professionals and policymakers to be one of the main barriers to the transition towards a circular economy. Digitisation is widely acknowledged as a catalyst for innovation in many sectors and digital technologies are driving new ways to exchange and share goods and services, enabling companies to match the supply, and demand for, otherwise underused assets and products. Online platforms, in particular, have played a crucial role in driving the growth of used goods and resale in other consumer goods markets, such as consumer technology. A mixed methods approach, including a review of 40 organisations operating second hand fashion models, a consumer survey of over 1200 respondents and in-depth interviews with 10 organisations operating second hand fashion models, is adopted to reveal (a) the barriers to consumer acceptance of reuse models in the fashion industry, and (b) how digital technologies can overcome these barriers. Findings highlight the significant progress that organisations have made in using digitalisation, including data analytics, algorithms, digital platforms, advanced product imagery and data informed customer communications, to address barriers associated with convenience, hygiene, trust and security. Furthermore, the study identifies opportunities for the development of more sophisticated digital technologies to support increased transparency and address concerns associated with the quality, authenticity and sourcing of materials. Positioned at the interface of digitisation and consumer acceptance of circular business models, this study makes an important contribution to understanding consumer barriers and how to address them and concludes with a set of recommendations for practitioners.

A Review of Endoscopic Spine Surgery: Decompression for Radiculopathy.

With this manuscript the authors sought to write a succinct review of the origins, as well as the latest advancements in endoscopic spine surgery to serve as a reference frame for physicians looking to learn this approach. At its infancy, the indications for posterolateral and transforaminal endoscopic decompression remained narrow, which prevented the procedure from gaining rapid traction during those days. However, more recently the tides have turned and an increasing number of surgeons are starting to adopt this technique given all its advantages. With the advent of higher quality camera systems and instruments, indications to use a minimally invasive option have gotten significantly broader. The most basic indication for the use of this technology is a soft disc herniation causing compromise of a neural structure that has failed to be managed successfully with non-surgical therapies. The use of endoscopic techniques provides significant advantages to patient outcomes and patient recovery. Endoscopic procedures should not be used as a blanket approach to nerve root decompression, as they certainly have limitations. Most contraindications to this procedure are relative and serve mostly as points to consider when selecting the methods to address neural compression. As these techniques become more widely accepted, we expect its reach and indications to continue to broaden and diversify. The full integration of navigation technologies will likely leapfrog this procedure into the mainstream use.

Contrast-enhanced Mammography: A Guide to Setting Up a New Clinical Program.

Contrast-enhanced mammography (CEM) is gaining rapid traction following the U.S. Food and Drug Administration approval for diagnostic indications. Contrast-enhanced mammography is an alternative form of mammography that uses a dual-energy technique for image acquisition after the intravenous administration of iodinated contrast material. The resulting exam includes a dual set of images, one that appears similar to a routine 2D mammogram and one that highlights areas of contrast uptake. Studies have shown improved sensitivity compared to mammography and similar performance to contrast-enhanced breast MRI. As radiology groups incorporate CEM into clinical practice they must first select the indications for which CEM will be used. Many practices initially use CEM as an MRI alternative or in cases recommended for biopsy. Practices should then define the CEM clinical workflow and patient selection to include ordering, scheduling, contrast safety screening, and managing imaging on the day of the exam. The main equipment requirements for performing CEM include CEM-capable mammography equipment, a power injector for contrast administration, and imaging-viewing capability. The main staffing requirements include personnel to place the intravenous line, perform the CEM exam, and interpret the CEM. To safely and appropriately perform CEM, staff must be trained in their respective roles and to manage potential contrast-related events. Lastly, informing referring colleagues and patients of CEM through marketing campaigns is helpful for successful implementation.

Energetic Performances Booster for Electric Vehicle Applications Using Transient Power Control and Supercapacitors-Batteries/Fuel Cell

In this paper, a hybrid electric power supply system for an electric vehicle (EV) is investigated. The study aims to reduce electric stress on the main energy source (fuel cell) and boost energetic performances using energy sources with high specific power (supercapacitors, batteries) for rapid traction chain solicitations such as accelerations, decelerations, and braking operations. The multisource EV power supply system contains a fuel cell stack, a lithium batteries module, and a supercapacitors (Sc) pack. In order to emulate the EV energy demand (wheels, weight, external forces, etc.), a bidirectional load based on a reversible current DC-DC converter was used. Fuel cell (Fc) stack was interfaced by an interleaved boost converter. Batteries and the Sc pack were coupled to the DC point of coupling via buck/boost converters. Paper contribution was firstly concentrated on the distribution of energy and power between onboard energy sources in consonance with their dynamic characteristics (time response). Second contribution was based on a new Sc model, which takes into consideration the temperature and the DC current ripples frequency until 1000 Hz. Energy management strategy (EMS) was evaluated by simulations and reduced scale experimental tests. The used driving cycle was the US Federal Test Procedure known as FTP-75.

Multi-agent deep reinforcement learning: a survey

The advances in reinforcement learning have recorded sublime success in various domains. Although the multi-agent domain has been overshadowed by its single-agent counterpart during this progress, multi-agent reinforcement learning gains rapid traction, and the latest accomplishments address problems with real-world complexity. This article provides an overview of the current developments in the field of multi-agent deep reinforcement learning. We focus primarily on literature from recent years that combines deep reinforcement learning methods with a multi-agent scenario. To survey the works that constitute the contemporary landscape, the main contents are divided into three parts. First, we analyze the structure of training schemes that are applied to train multiple agents. Second, we consider the emergent patterns of agent behavior in cooperative, competitive and mixed scenarios. Third, we systematically enumerate challenges that exclusively arise in the multi-agent domain and review methods that are leveraged to cope with these challenges. To conclude this survey, we discuss advances, identify trends, and outline possible directions for future work in this research area.

No Time to Waste: Real-World Repurposing of Generic Drugs as a Multifaceted Strategy Against COVID-19.

Real-world drug repurposing—the immediate “off-label” prescribing of drugs to address urgent clinical needs—is an indispensable strategy gaining rapid traction in the current COVID-19 crisis. Although off-label prescribing (ie, for a nonapproved indication) is legal in most countries, it tends to shift the burden of liability and cost to physicians and patients, respectively. Nevertheless, in urgent public health crises, it is often the only realistic source of a meaningful potential solution. To be considered for real-world repurposing, drug candidates should ideally have a track record of safety, affordability, and wide accessibility. Although thousands of such drugs are already available, the absence of a central repository of off-label uses presents a barrier to the immediate identification and selection of the safest, potentially useful interventions. Using the current COVID-19 pandemic as an example, we provide a glimpse at the extensive literature that supports the rationale behind six generic drugs, in four classes, all of which are affordable, supported by decades of safety data, and pleiotropically target the underlying pathophysiology that makes COVID-19 so dangerous. Having previously fast-tracked this paper to publication in summary form, we now expand on why cimetidine/famotidine (histamine type-2 receptor antagonists), dipyridamole (antiplatelet agent), fenofibrate/bezafibrate (cholesterol/triglyceride-lowering agents), and sildenafil (phosphodiesterase-5 inhibitor) are worth considering for patients with COVID-19 based on their antiviral, anti-inflammatory, renoprotective, cardioprotective, and anticoagulation properties. These examples also reveal the unlimited opportunity to future-proof public health by proactively mining, synthesizing, and cataloging the off-label treatment opportunities of thousands of safe, well-established, and affordable generic drugs.

Evaluating the Market Share of China Railway Express Lines – A Data-driven Approach

Fuelled by the Belt and Road Initiative, Eurasia railway transport has gained rapid traction. However, China Railway Express is in the development period, information about China Railway Express lines is in chaos, and it is difficult to appraise the market situation. This paper focuses on providing an approach to estimate the market share of every China Railway Express line. In this paper, the crawled data from the website are applied to estimate the customer demands for China Railway Express services in different areas of China. The government subsidy is a factor that cannot be ignored, but its level is unclear. Thus, a dummy regression model was established to estimate the subsidy. The regression result is in line with the data released by the Guangdong Provincial Government in 2017. To identify customers’ preferred choices for particular lines, a multi-objective optimization model has been built. With the crawled demands data and this optimization model, the current and future market share of China Railway Express can be assessed. If the subsidy is cancelled, some China Railway Express lines will lose their market, and only three lines have a bright future.

Highly-ordered assembly sheath layers of graphene coaxial fibers for high-performance wearable devices

Graphene fibers (GF) have broad application prospects in the fields of supercapacitors, electrodes, stimuli response sensors, and smart wearables. However, previously reported graphene-based fibers generally have low toughness and poor stretchability, which may limit possible applications. Here, we prepared novel high-strength, -stretch, and -conductivity graphene fibers with dense and highly-ordered sheath layers and a porous core structure. This was prepared by an efficient one-step coaxial wet-spinning method, which forms the rapid traction of the core layers on the sheath layers by the speed difference of the former, which is faster than the latter. The fiber surface was also subjected to the scouring force of the coagulation bath when the spinning solution was sprayed out of the spinning hole. The tug-of-war effect of these two opposing forces reacts on the curved graphene sheets, which made the graphene layers gradually straighten out, so that the sheath is efficiently and orderly aligned. The elongation of the high-strength GF with a core-sheath structure was effectively improved by approximately double, which was much higher than the previous research results. Moreover, high strength was maintained, and electrical stability was observably increased due to the core-sheath structure of the fibers. Such fibers also exhibited very stable electrical resistance during radial compression and tension cycles. Furthermore, we demonstrated the application of the fibers in wearable flexible devices.

Extrusão dentária rápida com finalidade protética – relato de caso

Root fractures cases, caries at the bone level, and root perforations impair the dental element due to the invasion of biological space, having in most cases the indication of tooth extraction. However, it is possible to evaluate the possibility of clinical coronary augmentation surgery in a functional way. However, in some cases, as in anterior teeth, it can impair aesthetics due to the new gingival positioning post-surgery. A more conservative and aesthetic alternative is to use extrusion techniques of the dental remnant for rehabilitation of the same without invasion of the biological space. In clinical situations involving biological spaces in the aesthetic region, the minimally invasive rapid vertical traction is indicated. Dental extrusion consists of the use of plaques, orthodontic appliances, and retainers that perform forced remnant traction for future prosthetic rehabilitation. The objective of this work is to demonstrate a case report with rapid extrusion of element 11 with endodontically treated root fracture through an acetate plate and orthodontic alloys, in order to make a fixed prosthesis later, allowing the preservation of the remaining tooth.

Analysis of orthopedic treatment of skeletal Class III malocclusion with Rapid Palatal Expansion and Face Mask therapy

Aim: To demonstrate the main effects on maxillary and facial profile after treatment with expansion and face mask therapy in patients pattern III Class III. Material and Method: A cross-sectional study of maxillary expansion and reverse traction performed in 4 patients with maxillary deficiency, in the pre-peak pubertal growth stage and in the mixed dentition, with cephalograms before and after treatment, using angular measurements (SNA, SNENA, ANL and 1NA) and linear (S’-ENA, S’-A, 1-NA, OVERJET, S-LS and S-LI) and plot overlays. Results: Improvement in overjet was observed, going from negative to positive in all cases treated with incisor uncrossing, although it was not statistically significant. The upper and lower labial posture with respect to the base of the nose and the ment improved significantly, represented by the measurements S-LS and S-LI, with a change from the concave profile to slightly convex. Conclusion: Class III malocclusion with maxillary deficiency treated with rapid maxillary disjunction and reverse traction with facial mask was effective in both groups, with maxillary protraction and shifting in the concave to slightly convex profile.KeywordsFacial Mask; Rapid maxillary expansion; Class III.

Supervised classification enables rapid annotation of cell atlases.

Single cell molecular profiling technologies are gaining rapid traction, but the manual process by which resulting cell types are typically annotated is labor-intensive and rate-limiting. We describe Garnett, an algorithm and accompanying software for rapidly annotating cell types in scRNA-seq and scATAC-seq datasets, based on an interpretable, hierarchical markup language of cell type-specific genes. Garnett successfully classifies cell types in tissue and whole organism datasets, as well as across species.