Splitting Approach Research Articles

Functional Split-Aware Optimal BBU Placement for 5G Cloud-RAN Over WDM Access/Aggregation Network

Fifth generation (5G) cloud-radio access network (C-RAN) aims at providing better performance and support to various applications with stringent data rate and latency requirements. In C-RAN, the processing units, known as the baseband units (BBUs), are segregated from the individual remote radio heads (RRHs) and moved to a convenient location to serve more than one RRH. This migration leads to an efficient resource allocation and cost-effective solution at the expense of a huge fronthaul traffic between the RRH and BBU hotel. The required fronthaul data rate largely depends on the employed functional split options. In this article, we propose a novel optimal BBU placement with a mixed functional split scheme to combat the fronthaul latency challenge while providing the network with greater flexibility and cost reduction. We introduce an integer linear programming (ILP)-based BBU placement problem with a mixed functional split selection approach to simultaneously minimize the number of BBU hotels and fibers, thereby reducing the network cost. Furthermore, a heuristic algorithm is proposed to solve the proposed model for large network scenarios. The obtained results show that an improvement of 25% and 50% is realized with the proposed scheme over the conventional fixed split option scheme for small and large network scenarios, respectively.

Well-Circumscribed Intramuscular Lipoma of Superior Rectus Muscle

Extraocular muscle lipoma is a rare benign mesenchymal tumor of the orbit. We report a case of a 37-year-old woman who presented with chronic progressive proptosis and inferior globe displacement of left eye. External eye examination revealed a yellowish mass at the superior bulbar conjunctiva. Magnetic resonance imaging showed a well-circumscribed mass confined in the superior rectus muscle belly and tendon with a fat signal. Debulking surgery was performed using the transconjunctival and vertical lid split approach. A pathological study demonstrated matured adipose tissue cells encapsulated by a thin layer of fibrous tissue, in addition to the chronic non-specific inflammation of the tenon capsule tissue sample. Histopathological findings of the mass were consistent with a well-circumscribed intramuscular lipoma. The symptoms of the patient were significantly improved 3 months after surgical and short-course systemic steroid treatments. However, long-term surveillance is needed.

A Hierarchical Multinomial Logit model to examine the effects of signal strategies on right-turn crash risks by crash movement configuration

Crash risk models relying on total crash counts are limited in their ability to extract meaningful insights regarding the context of crashes and to identify effective remedial measures. In addition to the typical classification of collisions noted in the literature (e.g., angle, head-on and rear-end), crashes can also be categorised according to vehicle movement configurations (Definitions for Coding Accidents or DCA codes in Australia). This classification presents an opportunity to extract useful insights into road traffic collision causes and contributing factors that are highly contextual. With this aim, this study develops crash-type models by DCA crash movement, with a focus on right-turn crashes (equivalent to left-turn crashes for right-hand traffic) at signalised intersections using a novel approach for linking crashes with signal control strategies. The modelling approach with contextual data enables quantification of the effect of signal control strategies on right-turn crashes, offering potentially unique and novel insights into right-turn crash causes and contributing factors.Crash-type models are estimated with the crash data of 218 signalised intersections in Queensland from 2012 to 2018. Multilevel (Hierarchical) Multinomial Logit Models with random intercepts are employed to capture the hierarchical influence of factors on crashes and unobserved heterogeneities. These models capture upper-level influences on crashes from intersection characteristics and lower-level influences from individual crash characteristics. The models specified in this way account for the correlation among crashes within intersections and influences on crashes across spatial scales. The model results reveal that the probabilities of the opposite approach crash type are significantly higher than the same direction and adjacent approach crash types for all right-turn signal control strategies at intersections except the split approach, for which the opposite is true. The results also suggest that the number of right-turning lanes and occupancy in conflicting lanes are positively associated with the likelihood of crashes for the same direction crash type.

Sustainable Development Goals: Therapeutic Entrepreneurship and Mental Health Conditions

This study analyzed therapeutic entrepreneurship and mental health condition in Nigeria. The study adopted quasi-experimental design and correlation design using systematic sampling and multi-stage cluster random sampling techniques. From the systematic population of 700 and sample size of 255 was determined using Slovin's formula at 0.05 level of significance, whereas 231 were deem fit after processing, retriever, coding and cleansing. The instrument was validated by experiential entrepreneurs and reliability was conducted using Split half approach. Three research questions and three hypotheses were raised which was tested using regression analysis on the likelihood test was utilized via SPSS 25 version. From the findings, therapeutic entrepreneurship discipline, therapeutic entrepreneurship risk-culture, therapeutic entrepreneurship passion, therapeutic entrepreneurship competence, therapeutic entrepreneurship capital, therapeutic entrepreneurship spirit, therapeutic entrepreneurship charisma strongly rehabilitates mental health conditions among clusters of entrepreneurs. In conclusion, the apriori expectations were found to be positively rehabilitation tendency outcomes among the sustainable development goals, therapeutic entrepreneurship components and mental health condition. Hence, the regression model revealed that the alternate hypotheses were accepted, while the null hypotheses. Based on the findings and conclusion, this study contributes to the knowledge that the entrepreneurs journey, dream and vision could not be threaten by mental disorderliness with credible understanding and application of the components of therapeutic entrepreneurship as instruments. It could be recommended that therapeutic entrepreneurship spirit, charisma and passion of entrepreneur should be assessed with the model intervention to rehabilitates mental illness. Also, the therapeutic entrepreneurship capital should be seen from the symbolic, intellectual, social and cultural capital, which should stands as drive to boost egos of entrepreneur’s well-being and wellness in climax of disorderliness.

Triceps Split and Snip Approach for Distal Humerus Fractures.

Background: The senior author adopted a Triceps Split and Snip approach in 2011. This paper details the results of patients for whom this approach was utilised for open reduction and internal fixation of complex AO type C distal humerus fractures. Methods: A retrospective analysis of a single surgeon's cases was conducted. Range of movement, as well as Mayo Elbow Performance Score (MEPS), and QuickDASH scores were evaluated. Two independent consultants with upper extremity practises evaluated pre- and post-operative radiographs. Results: Seven patients were available for clinical review. The mean age at the time of surgery was 47.7 years (range, 20.3-83.2) and the mean follow-up time was 3.6 years (range, 0.58-8). The average QuickDASH score was 15.85 (range, 0-52.3), average MEPS was 86.88 (range, 60-100) and average total arc of movement (TAM) was 103° (range, 70°-145°). All patients demonstrated 5/5 MRC triceps strength compared to the contralateral side. Conclusions: The Triceps Split and Snip approach for complex distal humerus fractures provided comparable mid-term clinical outcomes when compared to other published data regarding distal humerus fractures. It is versatile and does not compromise the intra-operative option of conversion to a total elbow arthroplasty. Level of Evidence: Level IV (Therapeutic).

Analisis Distribusi Suhu Permukaan pada Berbagai Penggunaan Lahan di Kota Kupang Provinsi Nusa Tenggara Timur

The increase of human population year by year cause the increase of land required to support human activities. It gives negative impacts to elements of the climate’s change. The research aimed to analyse the surface temperature changes on some type of closure of land and analyse the distribution of surface temperature using Landsat 8 Imagery of Kupang City, East Nusa Tenggara Province. This research methods applied Split Windows Algorithm approach. The result of this research found that the surface temperature changes tended to decrease from 2017 and 2021. The distribution of surface temperature from 2017-2021 has divided into four class intervals of temperature with the lowest temperature as much as ≤ 23 oC and the highest temperature of ≥45.37 oC.

A double sigmoidal model for snow-rain phase separation

This paper presents the use of a double sigmoidal model for precipitation phase partitioning in mountains. For the model development and evaluation, daily rainfall, minimum and maximum air temperatures, and snow depth data from twelve synoptic stations in the mountainous regions of Iran are used. The model performance is compared against six air temperature-based methods using the Taylor diagram, the coefficient of determination (R2), and the Root Mean Square Error (RMSE) performance indicators. Comparing the frequency of snowfall events estimated by the proposed model with those of the existing models and observation at the selected stations showed better performance of the proposed model in precipitation phase discrimination at the studied stations. The average R2 statistic that relates the frequency of snowfall occurrences estimated by the proposed model with the frequency of snowfall events observed at the studied stations is 0.989, which is the highest compared to other available models. Its average error across the stations is 4%, the lowest among the examined models. A split sample approach was used to ensure that the parameters of the proposed model are appropriately estimated. The result showed that the R2 and RMSE values of both calibration and validation subsets are not vastly different from each other, suggesting that the parameters of the two experiments are stable and the corresponding results are robust. The proposed model also performs better than other existing models in accurately estimating air temperature thresholds required for precipitation phase discrimination as well as the snow depth data in all studied stations.

Hybrid explicit–implicit learning for multiscale problems with time dependent source

The splitting method is a powerful method for solving partial differential equations. Various splitting methods have been designed to separate different physics, nonlinearities, and so on. Recently, a new splitting approach has been proposed where some degrees of freedom are handled implicitly while other degrees of freedom are handled explicitly. As a result, the scheme contains two equations, one implicit and the other explicit. The stability of this approach has been studied. It was shown that the time step scales as the coarse spatial mesh size, which can provide a significant computational advantage. However, the implicit solution part can still be expensive, especially for nonlinear problems. In this paper, we introduce modified partial machine learning algorithms to replace the implicit solution part of the algorithm. These algorithms are first introduced in ‘HEI: Hybrid Explicit-Implicit Learning For Multiscale Problems’, where a homogeneous source term is considered along with the Transformer, which is a neural network that can predict future dynamics. In this paper, we consider time-dependent source terms which is a generalization of the previous work. Moreover, we use the whole history of the solution to train the network. As the implicit part of the equations is more complicated to solve, we design a neural network to predict it based on training. Furthermore, we compute the explicit part of the solution using our splitting strategy. In addition, we use Proper Orthogonal Decomposition based model reduction in machine learning. The machine learning algorithms provide computational saving without sacrificing accuracy. We present three numerical examples which show that our machine learning scheme is stable and accurate.

A sagittal split osteotomy approach for removal of a large cementoblastoma at the mandibular angle

Benign lesions at the angle of mandible are frequently removed by a conventional intra oral approach to gain access and achieve complete visualisation. This method is quick and effective when dealing with small benign lesions that are superficially located at the angle of mandible. The removal of large and deeply located lesions with a conventional intra oral approach however, bring about a unique set of challenges particularly when the third molar is displaced towards the inferior border of mandible including lack of complete visualisation of the lesion, difficulty in identification and protection of the inferior alveolar nerve and necessitating removal of a considerable amount of osseous structure thus increasing the risk of a mandibular fracture. Alternative techniques for such lesions include an extra oral approach but one which could potentially create a cosmetic defect from cutaneous scarring and can result in facial nerve injury. This case report describes the use of a unilateral sagittal split osteotomy (SSO) in the removal of a mandibular cementoblastoma. This is a safe and effective technique allowing optimal access to the tumor with complete visualisation, identification and protection of the inferior alveolar nerve with minimal bone removal while maintaining mandibular integrity, strength and facial aesthetics.

A systematic scoping review of reflective writing in medical education

BackgroundReflective writing (RW) allows physicians to step back, review their thoughts, goals and actions and recognise how their perspectives, motives and emotions impact their conduct. RW also helps physicians consolidate their learning and boosts their professional and personal development. In the absence of a consistent approach and amidst growing threats to RW’s place in medical training, a review of theories of RW in medical education and a review to map regnant practices, programs and assessment methods are proposed.MethodsA Systematic Evidence-Based Approach guided Systematic Scoping Review (SSR in SEBA) was adopted to guide and structure the two concurrent reviews. Independent searches were carried out on publications featured between 1st January 2000 and 30th June 2022 in PubMed, Embase, PsychINFO, CINAHL, ERIC, ASSIA, Scopus, Google Scholar, OpenGrey, GreyLit and ProQuest. The Split Approach saw the included articles analysed separately using thematic and content analysis. Like pieces of a jigsaw puzzle, the Jigsaw Perspective combined the themes and categories identified from both reviews. The Funnelling Process saw the themes/categories created compared with the tabulated summaries. The final domains which emerged structured the discussion that followed.ResultsA total of 33,076 abstracts were reviewed, 1826 full-text articles were appraised and 199 articles were included and analysed. The domains identified were theories and models, current methods, benefits and shortcomings, and recommendations.ConclusionsThis SSR in SEBA suggests that a structured approach to RW shapes the physician’s belief system, guides their practice and nurtures their professional identity formation. In advancing a theoretical concept of RW, this SSR in SEBA proffers new insight into the process of RW, and the need for longitudinal, personalised feedback and support.

Reverse shoulder arthroplasty for proximal humerus fractures: a comparison of the deltoid split and deltopectoral approaches.

Reverse shoulder arthroplasty (RSA) is a common treatment for three- and four-part proximal humerus fractures. RSA is commonly performed through a deltopectoral (DP) surgical approach; however, a deltoid split (DS) approach has been described. The purpose of this study was to compare the intraoperative and postoperative outcomes of patients undergoing RSA for proximal humerus fractures through a DP and DS approach. A retrospective study of patients who underwent RSA for proximal humerus fractures at our level 1 trauma center was performed. Patients were evaluated at a minimum 1-year follow-up. Intraoperative outcomes as well as patient-reported outcome measures (PROMs) were analyzed. Postoperative complications, reoperation rates, and radiographic outcomes were evaluated. Sixteen patients were included in the DP group and 13 patients in the DS group. The average follow-up was 28.6months in the DP group and 21.1months in the DS group. There were no significant differences in patient demographics or injury characteristics. Operative time was significantly shorter in the DS group (103min) compared to the DP group (123min). Tuberosity repair was performed in 81.3% of patients in the DP group and 92.3% of patients in the DS group. No significant differences were found in PROMs at final follow-up. There were no significant differences in postoperative complications. Three patients in the DP group and one patient in the DS group required reoperation. Lastly, 81.8% of patients achieved tuberosity union in the DS group and 66.7% in the DP group; however, this did not reach statistical significance. This study demonstrates that RSA for proximal humerus fractures performed through a DS or DP approach may result in similar intraoperative and postoperative outcomes, with no difference in reoperation or complication rates.

Split modeling approach to non-cooperative strategic games

Split modeling approach to non-cooperative strategic games

Split CFD-simulation approach for effective quantification of mixed convective heat transfer coefficients on complex machine tool models

Split CFD-simulation approach for effective quantification of mixed convective heat transfer coefficients on complex machine tool models

The Combined Effect of Botulinum Toxin Type A with a Biorevitalizing Treatment on Forehead Rejuvenation: A Case Series

Background: The forehead is particularly prone to repetitive facial expressions and hyperdynamic activity, resulting in deep wrinkles and a loss of elasticity and hydration. Although botulinum toxin type A (BoNTA) has been shown to reduce the appearance of wrinkles and allow patients to have a smoother and hence younger upper face, it cannot help to improve the other aspects that determine overall skin quality. Objective: This case series aims to evaluate the clinical efficacy of combining BoNTA injections with a biorevitalizing treatment (NCTF®135HA) on skin aging signs and quality using a split face approach. Patients and Methods: A total of eight patients from 30 to 55 years old were treated with botulinum toxin type A combined with NCTF®-135HA or alone. Results: At D60, clinical skin quality scoring showed that NCTF®135HA injection significantly reduced wrinkles and enhanced skin homogeneity, hydration, firmness, and radiance. The Global Aesthetic Improvement Scale (GAIS) by the evaluator at D60 reported mean scores of 2375 (much improved) on the side of the face treated with BoNTA + NCTF®-135HA compared to the side of the face without NCTF®135HA. According to patients, the NCTF®135HA injections resulted in a significantly better aesthetic improvement score on D60 (mean score of 2.5 compared to 0.125 without NCTF®135HA, p 0.001). Conclusions: Our findings show that combining a biorevitalizing treatment with a BoNTA injection can significantly improve the skin’s overall appearance and decrease the wrinkle score when compared to the BoNTA injections alone. The results suggest that the combinatory strategy is effective, safe, and associated with a high level of patient satisfaction.

Subgroups and differences of fixation in 3-part proximal humerus fractures.

This study aimed to determine the morphological differences of three-part proximal humerus fractures, the group in which plate screw fixation is most frequently used, and to evaluate the functional and radiological results of the methods applied for different subgroups. Twenty-nine patients (6 males and 23 females) with three-part proximal humerus fractures were in the study, with an average age of 64. The patients were in three groups according to their fracture types. Group 1 included eight patients with valgus impaction fracture. Group 2 included eleven patients with easily achieved stability after reduction. Group 3 consisted of ten patients with procurvatum varus angulation, a significant displacement between fragments, and in whom medial cortical continuity was not maintained without fixation. All patients underwent surgery with a minimally invasive deltoid split approach method and locked ana-tomic plate screw osteosynthesis. In group 1 patients, the space in the area where valgization is present in the head was filled with cortico-cancellous allografts. No grafting or metaphyseal compression took place in Group 2 patients. In group 3 patients, the metaphyseal compression technique was applied to the bone defect area. Cephalodiaphyseal angles (CDA) were measured at the postoperative and final follow-up. The constant Murley score made the functional evaluation. The patients were followed for an average of 27.6 months, and the union was present in all patients for an average of 3.6 months. Early screw migration was present in three patients, and late screw migration was in one patient. There were twenty-four excellent and 5 good results. CDA decreased from 139.42° to 136.13°. A statistically significant difference was present between the values of Groups 2 and 3 in the final control CDA of the groups. In this study, the functional scores of grafting stable valgus-impacted fractures and metaphyseal compression of unstable fractures with insufficient medial support were as good as stable 3-part fractures. Considering neer type 3 fractures should be evaluated with their subgroups, and fixation and stability-enhancing solutions specific to the groups are essential.

Quantum Topology Optimization via Quantum Annealing

We present a quantum annealing-based solution method for topology optimization (TO). In particular, we consider TO in a more general setting, i.e., applied to structures of continuum domains where designs are represented as distributed functions, referred to as continuum TO problems. According to the problem's properties and structure, we formulate appropriate sub-problems that can be solved on an annealing-based quantum computer. The methodology established can effectively tackle continuum TO problems formulated as mixed-integer nonlinear programs. To maintain the resulting sub-problems small enough to be solved on quantum computers currently accessible with small numbers of qubits and limited connectivity, we further develop a splitting approach that splits the problem into two parts: the first part can be efficiently solved on classical computers, and the second part with a reduced number of variables is solved on a quantum computer. By such, a practical continuum TO problem of varying scales can be handled on the D-Wave quantum annealer. More specifically, we concern the minimum compliance, a canonical TO problem that seeks an optimal distribution of materials to minimize the compliance with desired material usage. The superior performance of the developed methodology is assessed and compared with the stateof-the-art heuristic classical methods, in terms of both solution quality and computational efficiency. The present work hence provides a promising new avenue of applying quantum computing to practical designs of topology for various applications.

Estimating the location of the posterior interosseus nerve during an extensor digitorum communis-splitting approach: a comparison of methods using the transepicondylar distance.

The posterior interosseus nerve (PIN) may be encountered when using the extensile extensor digitorum communis (EDC)-splitting approach to the elbow. An accurate means of estimating its location remains elusive. The purpose of this investigation is to identify whether the methods described in previous studies can be improved upon to more accurately estimate the PIN's location using the transepicondylar distance (TED). Forty-five fresh-frozen cadavers were dissected using the EDC-splitting approach. Method A (N=39) used an electronic caliper measuring along the midlateral border of the radius from the lateral epicondyle (LE) and radiocapitellar joint in supination, neutral position, and pronation. Method B (N=16) used a sterile tape measure, measuring from the LE in pronation only along an axis from the LE to Lister's tubercle passing through the center capitellum. In method A, the mean TED was 63.4±6.1 mm. Of the 6 measurements, the TED was most correlated to the actual distance to the PIN from the LE in pronation (68.3±7.3 mm; R2=0.266). The median difference between the estimated and actual distances was -5.6 mm (-19.3 mm to 7.6 mm). In method B, the mean TED was 68.4±8.7 mm, and the mean measured distance from the LE in pronation was 68.7±9.4 mm. The TED closely correlated with the measured distance to the PIN (R2=0.95, P<.001). The mean difference between the estimated and actual distances was ±2.0 mm (range -4.0 mm to2.0 mm), significantly more precise than method A (P=.007). Using a tape measure, the TED predicted the PIN's location within a mean ±2 mm in pronation along an axis from the LE to Lister's tubercle, using an EDC-splitting approach. This technique is simple and comparatively more accurate than those used previously.

Maxillary Ridge Split with Simultaneous Implant Placement – A Case Report

Inadequate alveolar ridge width often poses difficulty in implant placement. Such ridges require a combination of techniques in placing implants. One such technique is the ridge split technique which helps the expansion of the ridge with or without greenstick fracture of cortical plates. Before placing implants the width of the alveolar ridge can be effectively restored utilising the modified ridge splitting approach employing autologous bone grafts. This case report describes the ridge splitting and placement of a dental implant in the left maxillary central region followed by guided bone regeneration. Ridge expansion was done in relation to 21 and osteotomy was prepared to the desired depth. After proper treatment planning implant measuring 3.5 mm in diameter and 11.5 mm in length was placed. Four months later final cementation was done with PFM crown. The ridge split technique with the immediate implant placement resulted in minimal resorption of alveolar bone along with maximum expansion of the bone. The sequential surgical and restorative techniques were combined into one successful protocol whose steps are well elaborated in this case report.

Exploiting machine learning methods with monthly routine milk recording data and climatic information to predict subclinical mastitis in Italian Mediterranean buffaloes

Mastitis has detrimental effects on the world's dairy industry, reducing animal health, milk production and quality, as well as income for farmers. In addition, consumers' growing interest in food safety and rational usage of antibiotics highlights the need to develop novel strategies to improve mastitis detection, prevention, and management. In the present study we applied machine learning (ML) analyses to predict presence or absence of subclinical mastitis in Italian Mediterranean buffaloes, exploiting information collected the previous month during routine milk recording procedures, as well as climatic data. The data set included 3,891 records of 1,038 buffaloes from 6 herds located in Basilicata Region (South Italy). Prediction models were developed using 4 different ML algorithms (Generalized Linear Model, Support Vector Machines, Random Forest, and Neural Network) and 2 data set splitting approaches for the creation of the training and test sets (by record or by animal ID number, always with 80% of the data used for model training and the remaining 20% for model testing). Support Vector Machine was the best method to predict high or low somatic cell count at the subsequent test-day record in the validation set, and therefore it was used to estimate the contribution of each feature to the best model. Independently from the data set splitting approach, the most important features were somatic cell score, differential somatic cell count, electrical conductivity, and milk production. Among climatic data, the most informative were temperature and relative humidity. When the data were split by animal ID, an improvement in models' predictive performance on the test set was observed, suggesting this as the most appropriate data splitting approach in data sets with repeated measures to avoid data leakage. According to different metrics, Neural Network was the best method for making predictions on the test set. Our findings confirmed the promising role of ML methods to improve prevention and surveillance of subclinical mastitis, exploiting the large amount of data currently available to identify animals that would possibly have high somatic cell count the subsequent month.

GAPS IN THE ANTI-TERRORISM FUNCTION OF THE EMERCOM OF RUSSIA

In order to increase the effectiveness of the participation of the Russian Emergencies Ministry in countering terrorism, including nuclear (radiological) terrorism, based on the methods of interpretation of legal norms, comparative legal and system analysis of regulatory legal acts and the content of basic concepts regulating the competence of authorities, the author revealed a mismatch of functions EMERCOM of Russia and its territorial bodies. An analysis of the elements of legal norms on countering terrorism in the activities of the Ministry and its subordinate bodies shows a split approach to the entire system and its individual structural elements. The results of a comparative law study of legal relations in the field of countering terrorism demonstrate disproportions in the main functions of the Main Directorates for the constituent entities of the Russia and the Ministry itself, the mismatch of departmental competence with the norms of basic anti-terrorist legislation, which is reflected in the quality and completeness of their implementation in practice. Therefore, the author proposes to clarify departmental functions in accordance with the current legislation of the Russia and make appropriate changes to the Decree of the President of the Russia of July 11, 2004 No. 868.