A survey of South African Maxillofacial & Oral Surgeon opinions regarding the academic education in the field of cleft lip/palate and craniofacial deformities

Maxillofacial and oral surgeons (MFOS) are trained to manage hard and soft tissue conditions affecting the orofacial region. They, therefore, play an essential role in the health care of  cleft lip/palate (CLP) and craniofacial deformities (CFD) patients. The complex and lengthy nature of CLP and CFD management requires collaboration between different disciplines. Consequently, it becomes increasingly important that the academic education available to MFOS provides in-depth knowledge, multidisciplinary participation and adequate clinical exposure provided by field experts. This study aimed to investigate the exposure and knowledge level of MFOS regarding the management of CLP and CFD. A second objective was to obtain an opinion from practising MFOS about the academic educational needs of those working with CLP and CFD. An online survey and telephone interviews (using a structured questionnaire) were used to investigate the level and scope of the MFOS academic education and to determine their academic needs. The questionnaire was completed by 53 (of 121)  of practising MFOS on the Medpages health care provider database, 64.8% of whom had more than 10 years of professional experience. Of the respondents, 60% showed a good general knowledge of CLP and CFD. However, 66.5% acknowledged that they had received only limited clinical training and exposure, which prevented them from providing adequate services to CLP/CFD patients. Only 41% of the respondents offered primary and/or only secondary treatment for both CLP and CFD patients, and 53.8% of them had participated in multidisciplinary teams. All the respondents agreed on the need for a dedicated training programme(s) in CLP and CFD management, and the majority recommended a subspecialty training either by degree courses or clinical fellowship and / or certification. This study demonstrates that postgraduate academic training and clinical exposure are limited in the CLP and CFD fields. All the respondents agreed that an educational strategy to meet the needs of MFOS providing CLP and CFD care should be established. Participants suggested that part-time clinical and/or degree courses should be developed

The orthodontist's views regarding academic education in cleft lip and palate as well as craniofacial deformities in South Africa

Orthodontists are essential members of a craniofacial team (American Cleft Palate-Craniofacial Association Team Standards Committee).1 Because cleft lip/palate (CLP) and craniofacial deformities (CFD) vary in severity and facial growth patterns, treatment is complex and lengthy and requires collaboration among different disciplines. Consequently, orthodontists need specialised training in this field to reach the treatment goals of good facial growth, aesthetically acceptable appearance, and dental occlusion. Therefore, it becomes increasingly important to provide adequate training for orthodontists, so they can not only provide efficient treatment but can also undertake a leadership role in the field. To obtain information regarding:• the CLP and CFD academic education of orthodontists the professional services that orthodontists offer to CLP and CFD patients• the educational and training needs of orthodontists in this field A 54-item online survey to collect quantitative data was conducted by means of an interview, using a randomised sample of orthodontists attending the annual scientific conference of the South African Society of Orthodontics. The questionnaire was completed by 53 orthodontists, 54.6% of whom had more than 10 years of professional experience. Of the respondents, 84.8% experienced some clinical exposure in this field during their postgraduate education. Treatment for CLP and CFD patients was offered by 92% of the professionals, but only 21.7% had high confidence in their expertise in treating CLP/CFD patients. Of the respondents, 88% agreed there was a need to improve CLP and CFD education, and the majority recommended fellowship training and certified courses. The rest suggested continuing-education workshops. Most of the orthodontists provided treatment for both CLP and CFD patients despite some of them lacking confidence in treating such cases. The majority agreed that there is a strong need to establish an educational strategy to meet the needs of orthodontists who treat CLP and CFD patients. The respondents suggested that programmes such as fellowship training, degree couses, certified courses, and continuing education workshops could be used

A Dual-Functional Massive MIMO OFDM Communication and Radar Transmitter Architecture

In this study, a dual-functional radar and communication (RadCom) system architecture is proposed for application at base-stations (BSs), or access points (APs), for simultaneously communicating with multiple user equipments (UEs) and sensing the environment. Specifically, massive multiple-input multiple-output (mMIMO) communication and orthogonal frequency-division multiplexing (OFDM)-based MIMO radar are considered with the objective to jointly utilize channel diversity and interference. The BS consists of a mMIMO antenna array, and radar transmit and receive antennas. Employing OFDM waveforms for the radar allows the BS to perform channel state information (CSI) estimation for the mMIMO and radar antennas simultaneously. The acquired CSI is then exploited to predict the radar signals received by the UEs. While the radar transmits an OFDM waveform for detecting possible targets in range, the communication system beamforms to the UEs by taking into account the predicted radar interference. To further enhance the capacity of the communication system, an optimum radar waveform is designed. Moreover, the network capacity is mathematically analyzed and verified by simulations. The results show that the proposed RadCom can achieve higher capacity than conventional mMIMO systems by utilizing the radar interference while simultaneously detecting targets

Optimized Precoders for Massive MIMO OFDM Dual Radar-Communication Systems

This paper considers the optimization of a dual-functional radar and communication (RadCom) system with the objective is to maximize its sum-rate (SR) and energy-efficiency (EE) while satisfying certain radar target detection and data rate per user requirements. To this end, novel RadCom precoder schemes that can exploit downlink radar interference are devised for massive multiple-input-multiple-output (MIMO) orthogonal frequency-division multiplexing (OFDM) systems. First, the communication capacity and radar detection performance metrics of these schemes are analytically evaluated. Then, using the derived results, optimum beam power allocation schemes are deduced to maximize SR and EE with modest computational complexity. The validity of the analytical results is confirmed via matching computer simulations. It is also shown that, compared to benchmark techniques, the devised precoders can achieve substantial improvements in terms of both SR and EE

A Dual-Functional Massive MIMO OFDM Communication and Radar Transmitter Architecture

In this study, a dual-functional radar and communication (RadCom) system architecture is proposed for application at base-stations (BSs), or access points (APs), for simultaneously communicating with multiple user equipments (UEs) and sensing the environment. Specifically, massive multiple-input multiple-output (mMIMO) communication and orthogonal frequency-division multiplexing (OFDM)-based MIMO radar are considered with the objective to jointly utilize channel diversity and interference. The BS consists of a mMIMO antenna array, and radar transmit and receive antennas. Employing OFDM waveforms for the radar allows the BS to perform channel state information (CSI) estimation for the mMIMO and radar antennas simultaneously. The acquired CSI is then exploited to predict the radar signals received by the UEs. While the radar transmits an OFDM waveform for detecting possible targets in range, the communication system beamforms to the UEs by taking into account the predicted radar interference. To further enhance the capacity of the communication system, an optimum radar waveform is designed. Moreover, the network capacity is mathematically analyzed and verified by simulations. The results show that the proposed RadCom can achieve higher capacity than conventional mMIMO systems by utilizing the radar interference while simultaneously detecting targets

Surface charge change in carbonates during low-salinity imbibition

Optimizing the injection water salinity could present a cost-effective strategy for improving oil recovery. Although the literature generally acknowledges that low-salinity improves oil recovery in laboratory-scale experiments, the physical mechanisms behind it are controversial. While most experimental low-salinity studies focus on brine composition, this study investigated the influence of carbonate rock material on surface charge change, wettability alteration, and spontaneous imbibition behavior. Zeta potential measurements showed that each tested carbonate rock material exhibits characteristic surface charge responses when exposed to Formation-water, Seawater, and Diluted-seawater. Moreover, the surface charge change sensitivity to calcium, magnesium, and sulfate ions varied for the tested carbonate materials. Spontaneous imbibition tests led to high oil recovery and, thus, wettability alteration towards water-wet conditions if the carbonate-imbibing brine system’s surface charge decreased compared to the initial zeta potential of the carbonate Formation-water system. In the numerical part of the presented study, we find that it is essential to account for the location of the shear plane and thus distinguish between the numerically computed surface charge and experimentally determined zeta potential. The resulting model numerically reproduced the experimentally measured calcium, magnesium, and sulfate ion impacts on zeta potential. The spontaneous imbibition tests were history-matched by linking surface charge change to capillary pressure alteration. As the numerical simulation of the laboratory-scale spontaneous imbibition tests is governed by molecular diffusion (with a time scale of weeks), we conclude that molecular diffusion-driven field scale wettability alteration requires several hundred years.publishedVersio

The structures of secretory and dimeric immunoglobulin A

Secretory (S) Immunoglobulin (Ig) A is the predominant mucosal antibody, which binds pathogens and commensal microbes. SIgA is a polymeric antibody, typically containing two copies of IgA that assemble with one joining-chain (JC) to form dimeric (d) IgA that is bound by the polymeric Ig-receptor ectodomain, called secretory component (SC). Here, we report the cryo-electron microscopy structures of murine SIgA and dIgA. Structures reveal two IgAs conjoined through four heavy-chain tailpieces and the JC that together form a β-sandwich-like fold. The two IgAs are bent and tilted with respect to each other, forming distinct concave and convex surfaces. In SIgA, SC is bound to one face, asymmetrically contacting both IgAs and JC. The bent and tilted arrangement of complex components limits the possible positions of both sets of antigen-binding fragments (Fabs) and preserves steric accessibility to receptor-binding sites, likely influencing antigen binding and effector functions

Comparative Study of Stock Trend Prediction using Time Delay, Recurrent and Probabilistic Neural Networks

Three networks are compared for low false alarm stock trend predictions. Short-term trends, particularly attractive for neural network analysis, can be used profitably in scenarios such as option trading, but only with significant risk. Therefore, we focus on limiting false alarms, which improves the risk/reward ratio by preventing losses. To predict stock trends, we exploit time delay, recurrent, and probabilistic neural networks (TDNN, RNN, and PNN, respectively), utilizing conjugate gradient and multistream extended Kalman filter training for TDNN and RNN. We also discuss different predictability analysis techniques and perform an analysis of predictability based on a history of daily closing price. Our results indicate that all the networks are feasible, the primary preference being one of convenienc

Comparison of Direct Fluorescence Assay and Real-Time RT-PCR as Diagnostics for Respiratory Syncytial Virus in Young Children

Respiratory syncytial virus (RSV) is the major cause of lower respiratory tract infections in children worldwide. Early detection of RSV is critical to initiate proper care. Two methods, the direct fluorescence assay (DFA) and the real-time reverse-transcription polymerase chain reaction (rt-RT-PCR), that are used for RSV detection were compared. A total of 451 nasopharyngeal aspirates from children 5 years of age or less were tested for RSV using both methods. The overall prevalence rate of the RSV among the children was 23.7% with a significantly higher prevalence among children under the age of 6 months of age when compared to other age groups. The sensitivity of DFA in comparison to rt-RT-PCR was highest (86%) during the first 3 days of symptoms onset and decreased gradually till it reached 65% after the first week. The specificity of DFA in comparison to rt-RT-PCR ranged between 99 and 100% irrespective of the date of collection. We concluded that, although the rt-RT-PCR is more sensitive for RSV detection, the DFA offers a reliable point-of-care alternative detection method especially during the first few days of illness

Predictive Head Tracking for Virtual Reality

In virtual reality (VR), head movement is tracked through inertial and optical sensors. Computation and communication times result in delays between measurements and updating of the new frame in the head mounted display(HMD). These delays result in problems, including motion sickness. We use recurrent and time delay neural networks to predict the head location and use it to calculate the new frame. A predictability analysis is used in designing the prediction syste