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Facial reconstruction following Mohs excision presents many challenges. The unpredictable nature of Mohs surgery can yield surprising deficits that require far more extensive reconstructions than originally anticipated. It is up to the reconstructive surgeon to guide the patient through the shock of the excision, initial reconstruction, definitive reconstruction, and postoperative management. It is essential to approach a post-Mohs patient with the understanding that a rushed, same-day reconstruction carries a greater risk for the patient and the outcome than that of a delayed, planned reconstruction. Considering factors beyond the deficits, such as the patient's means, health literacy, and comorbidities, is essential to ensuring a methodical reconstruction with favorable results. Often, deficits will need to be temporized until the patient is optimized and the details of the reconstruction have been established. The specifics of the reconstruction are heavily influenced by the patient's desires, understanding, and ability to participate multistage operations. Once the best suited reconstruction is selected, reviewing expectations and the possible associated contingencies is crucial for patient satisfaction. Despite the surgeon's great effort in ensuring a satisfactory reconstruction, many patients will further benefit from close follow-up and postoperative scar management. The combination of patient optimization, meticulous surgical planning, and postoperative wound management enables the surgeon to obtain favorable outcomes, even in the most unpredictable reconstructions. [ABSTRACT FROM AUTHOR]

This study aimed to achieve the incidence, phenotypic characterization, virulence potential, and genetic diversity of B. cereus sensu lato group in raw bulk tank milk (BTM) and mastitic milk, with special concern to the B. cereus sensu stricto (s.s.). Milk samples including122 bulk tank milk (BTM) and 67 clinically mastitic cow's milk were screened for the existence of B. cereus s.l. group. B. cereus s.s. were isolated and PCR-confirmed with a prevalence of 31.7%. Thirty-two isolates displayed typical morphology, while 28 isolates displayed atypical morphology. Among isolates, 93.4, 46.7 and 85% were hemolytic, biofilm, and slime producers, respectively. The most prevalent toxin genes were cyt-k, bceT and nhe genes in percentages of 86.7, 85, and 46.7%, respectively. One isolate harbored ces-gene (1.7%). Also, 53.3% and 50 % of B. cereus s.s. isolates harbored tasA and sipW genes, respectively. Comparing typical and atypical isolates revealed that 100% of typical isolates were hemolytic versus 85.7% of atypical isolates, 53.1% and 78.1% of typical isolates were biofilm and slime producers versus 39.3% and 92.9% of atypical ones. Nine toxin gene profiles were found. Prevalences of toxin and biofilm-related genes in typical isolates were 53.1, 84.4, 93.8, 0, 46.9 and 46.9 % for nhe, cyt K, bceT, ces, tasA, and sipW genes versus 39.3, 89.3, 75, 3.6, 60.7 and 53.57% in atypical isolates. The obtained finding demonstrated the presence of potentially pathogenic B. cereus s.s. in milk. The isolation of atypical forms of B. cereus s.s. which weren't less virulent than the typical form was confirmed. Therefore, efforts should be made to prevent their misdiagnosis in dairy plants. [ABSTRACT FROM AUTHOR]

To address the problem of sparse data and cold-start when facing new users and items in the single-domain recommendation, cross-domain recommendation has gradually become a hot topic in the recommendation system. This method enhances target domain recommendation performance by incorporating relevant information from an auxiliary domain. A critical aspect of cross-domain recommendation is the effective transfer of user preferences from the source to the target domain. This paper proposes a novel cross-domain recommendation framework, namely the Cross-domain Recommendation based on Aspect-level Sentiment extraction (CRAS). CRAS leverages user and item review texts in cross-domain recommendations to extract detailed user preferences. Specifically, the Biterm Topic Model (BTM) is utilized for the precise extraction of 'aspects' from users and items, focusing on identifying characteristics that align with user interests and the positive attributes of items. These 'aspects' represent distinct, influential features of the items. For example, a good service attitude can be regarded as a good aspect of a restaurant. Furthermore, this study employs an improved Cycle-Consistent Generative Adversarial Networks (CycleGAN), efficiently mapping user preferences from one domain to another, thereby enhancing the accuracy and personalization of the recommendations. Lastly, this paper compares the CRAS model with a series of state-of-the-art baseline methods in the Amazon review dataset, and experiment results show that the proposed model outperforms the baseline methods. [ABSTRACT FROM AUTHOR]

The article discusses the use of a synthetic dermal matrix called NovoSorb biodegradable temporizing matrix (BTM) in reconstructing complex oncologic defects. BTM consists of a biodegradable polyurethane foam with a non-biodegradable sealing membrane, promoting neodermis formation and wound closure. The article presents three cases where BTM was successfully used for oncologic defect reconstruction, highlighting its advantages in restoring dermal thickness, reducing contracture, and providing rapid coverage for large areas. The study emphasizes BTM's resilience against infection, rapid integration within 2 weeks, and potential applications beyond oncologic defects, such as in necrotizing fasciitis and extensive burns. [Extracted from the article]

Synthetic Biodegradable Temporising Matrix (BTM, NovoSorb; PolyNovo Biomaterials Pty Ltd, Port Melbourne, Victoria, Australia) has proven useful in the resurfacing of large burns,1 necrotising infection debridement2 and tumour excision with exposed bone.3 We present a case report of a large BCC invading three aesthetic subunits of the face which was successfully reconstructed with BTM, split-thickness skin graft with subsequent adjuvant radiotherapy due to the high risk nature of the BCC. We present our series of images illustrating the timeline of BTM, and the ability to achieve a good skin colour match with minimal contour deformity, even in the event of post operative radiotherapy use.

Purpose: In pediatric population, large soft tissue defects occur in avulsion injuries. In addition to the challenges of primary surgical therapy, elasticity, appearance and function of the scar in children are of crucial importance, especially in the context of body growth. So far various flaps, plasties, skin grafts and dermal substitutes have become established, although infections and skin shrinkage remain challenging. In 2020, a new skin substitute material—NovoSorb® Biodegradable Temporizing Matrix (BTM)—was introduced in Europe for temporary wound closure and tissue regeneration. The aim of this study was to evaluate the value of BTM in pediatric patients. Methods: The study included all children treated with BTM after traumatic soft tissue defects following limb avulsion injuries between June 2021 and June 2023 at a university hospital. Results: 7 patients with limb avulsion injuries were treated with BTM, 4 boys, 3 girls. Mean age was 6.5 years (2–11 years) at the time of BTM placement. 4/7 had concomitant fractures. BTM was used successfully in all cases, infection did not occur, skin shrinkage was seen in one case. Split thickness skin graft (STSG) after BTM application was performed in average after 33 days (26 to 39 days). Limitations of this study were highlighted. Conclusion: BTM is a promising alternative for reconstruction of complex trauma extremity wounds in children following avulsion injuries, even in cases of concomitant bone injuries. Interpretation may be limited by sample size. [ABSTRACT FROM AUTHOR]

Background & aimsLiver disease carries significant healthcare burden and frequently requires a combination of blood tests, imaging, and invasive liver biopsy to diagnose. Distinguishing between inflammatory liver diseases, which may have similar clinical presentations, is particularly challenging. In this study, we implemented a machine learning pipeline for the identification of diagnostic gene expression biomarkers across several alcohol-associated and non-alcohol-associated liver diseases, using either liver tissue or blood-based samples.MethodsWe collected peripheral blood mononuclear cells (PBMCs) and liver tissue samples from participants with alcohol-associated hepatitis (AH), alcohol-associated cirrhosis (AC), non-alcohol-associated fatty liver disease, chronic HCV infection, and healthy controls. We performed RNA sequencing (RNA-seq) on 137 PBMC samples and 67 liver tissue samples. Using gene expression data, we implemented a machine learning feature selection and classification pipeline to identify diagnostic biomarkers which distinguish between the liver disease groups. The liver tissue results were validated using a public independent RNA-seq dataset. The biomarkers were computationally validated for biological relevance using pathway analysis tools.ResultsUtilizing liver tissue RNA-seq data, we distinguished between AH, AC, and healthy conditions with overall accuracies of 90% in our dataset, and 82% in the independent dataset, with 33 genes. Distinguishing 4 liver conditions and healthy controls yielded 91% overall accuracy in our liver tissue dataset with 39 genes, and 75% overall accuracy in our PBMC dataset with 75 genes.ConclusionsOur machine learning pipeline was effective at identifying a small set of diagnostic gene biomarkers and classifying several liver diseases using RNA-seq data from liver tissue and PBMCs. The methodologies implemented and genes identified in this study may facilitate future efforts toward a liquid biopsy diagnostic for liver diseases.Lay summaryDistinguishing between inflammatory liver diseases without multiple tests can be challenging due to their clinically similar characteristics. To lay the groundwork for the development of a non-invasive blood-based diagnostic across a range of liver diseases, we compared samples from participants with alcohol-associated hepatitis, alcohol-associated cirrhosis, chronic hepatitis C infection, and non-alcohol-associated fatty liver disease. We used a machine learning computational approach to demonstrate that gene expression data generated from either liver tissue or blood samples can be used to discover a small set of gene biomarkers for effective diagnosis of these liver diseases.

Objectives: Addressing extensive and deep burn wounds poses considerable challenges for both patients and surgeons. The NovoSorb® Biodegradable Temporizing Matrix (BTM) emerged as a novel dermal substitute and has been subjected to evaluation in large burn wound cases, with a specific focus on identifying risk factors associated with suboptimal take rates. Methods: All patients with burn wounds greater than 10% body surface that underwent BTM treatment between March 2020 and November 2023 were eligible for inclusion. Univariate analyses and linear regression models were employed to discern risk factors and predictors influencing the take rates of both the BTM and split-thickness skin grafts (STSGs). Results: A total of 175 patients (mean age 56.2 ± 19.8 years, 70.3% male) were evaluated. The mean take rates of the BTM and STSGs were 82.0 ± 24.7% and 87.3 ± 19.0%, respectively. There were significant negative correlations between BTM take and the number of surgeries before BTM application (r = −0.19, p = 0.01), %TBSA and STSG take (r = −0.36, p = <0.001) and significant positive correlations between BTM and STSG take (r = 0.41, p ≤ 0.001) in addition to NPWT and STSG take (r = 0.21, p = 0.01). Multivariate regression analyses showed that a larger number of surgeries prior to BTM application (OR −3.41, 95% CI −6.82, −0.03, p = 0.04) was associated with poorer BTM take. Allograft treatment before BTM application (OR −14.7, 95% CI −23.0, −6.43,p = 0.01) and failed treatment with STSG before BTM application (OR −20.8, 95% CI −36.3, −5.23, p ≤ 0.01) were associated with poorer STSG take, whereas higher BTM take rates were associated with overall higher STSG take (OR −0.15, 95% 0.05, 0.26, p = 0.01). The Meek technique was used in 24 patients and showed similar take rates (BTM: 76.3 ± 28.0%, p = 0.22; STSG: 80.7 ± 21.1, p = 0.07). Conclusions: This study summarizes our findings on the application of a BTM in the context of large burn wounds. The results demonstrate that successful treatment can be achieved even in patients with extensive burns, resulting in satisfying take rates for both the BTM and STSG. The data underscore the importance of promptly applying a BTM to debrided wounds and indicate good results when using Meek. [ABSTRACT FROM AUTHOR]

Extensive full-thickness soft-tissue defects remain a challenge in reconstructive surgery. NovoSorb® Biodegradable Temporising Matrix (BTM) represents a novel dermal substitute and was evaluated in wounds deriving from different aetiologies and to highlight risk factors for poor take rates. All patients treated with BTM at our department between March 2020 and October 2022 were included. Differences in univariate and linear regression models identified predictors and risk factors for take rates of BTM and split-thickness skin grafts (STSG). Three hundred patients (mean age 54.2 ± 20.1 years, 66.3% male, 59.7% burns, 19.7% trauma and 20.6% others) were evaluated. Mean take rates of BTM and STSG after BTM delamination were 82.7 ± 25.2% and 86.0 ± 22.6%, respectively. Multiple regression analyses showed that higher body mass index (BMI, OR 0.43, 95% CI 0.86, −0.01, p = 0.44), prior allograft transplantation (OR 15.12, 95% CI 26.98, −3.31, p = 0.041), longer trauma-to-BTM-application intervals (OR 0.01, 95% CI 0.001, −0.001, p = 0.038), positive wound swabs before BTM (OR 7.15, 95% CI 13.50, −0.80, p = 0.028) and peripheral artery disease (OR 10.80, 95% CI 18.63, −2.96, p = 0.007) were associated with poorer BTM take. Higher BMI (OR 0.40, 95% CI 0.76, −0.08, p = 0.026), increasing BTM graft surface areas (OR 0.58, 95% CI −1.00, −0.17, p = 0.005), prior allograft (OR 12.20, 95% CI −21.99, −2.41, p = 0.015) or autograft transplantations (OR 22.42, 95% CI 38.69, −6.14, p = 0.001), tumour as the aetiology of the wound (OR 37.42, 95% CI 57.41, −17.83, p = 0.001), diabetes (OR 6.64, 95% CI 12.80, −0.48, p = 0.035) and impaired kidney function (OR 5.90, 95% CI 10.94, −0.86, p = 0.021) were associated with poorer STSG take after delamination of BTM, whereas higher BTM take rates were associated with better STSG take (OR 0.40, 95% CI 0.31,0.50, p < 0.001). Extensive complex wounds of different aetiologies unsuitable for immediate STSG can be successfully reconstructed by means of two-staged BTM application and subsequent skin grafting. Importantly, presence of wound contamination or infection and prior allograft coverage appear to jeopardise good BTM and STSG take. [ABSTRACT FROM AUTHOR]

This case series reviews the management of 2 patients who developed a rare, aggressive soft tissue infection, necrotizing fasciitis treated with a synthetic polyurethane dermal regenerative template, Biodegradable Temporizing Matrix (NovoSorb BTM) in conjunction with an off-label use of RECELL device applying autologous skin cell suspension and a split-thickness skin graft for reconstruction. The clinical relevance describes a non-traditional patient's course of treatment and clinical outcome using BTM and RECELL for necrotizing fasciitis. The 2 patients survived with acceptable outcomes and timely healing despite a high chance of mortality and likely amputation secondary to the extensive surface area and anatomical location of the infection. [ABSTRACT FROM AUTHOR]

Summary: We present the case of a 65 year old man who sustained a complex dorsal hand degloving injury with segmental loss of EDC tendon to middle finger, which was reconstructed using BTM. He returned to near full function despite not having a tendon reconstruction, and the uninjured tendons were able to glide without restriction beneath the BTM. We review the case and the literature surrounding the use of BTM in this clinical scenario.

In contemporary distribution networks (DNs), characterized by extensive integration of distributed energy, the photovoltaic (PV) power output data from the distribution station areas become crucial for system planning and operational optimization. Since many PVs are installed behind-the-meter (BTM), it is difficult to directly obtain PV power data through measurement devices. Therefore, it is important to estimate the BTM PV power from the aggregating data that can be directly obtained. However, the existing estimation methods usually require centralized large-scale data training, which brings certain privacy leakage risks. In order to solve these problems, we propose a federated learning-based improved Transformer Neural Network strategy to estimate BTM PV generation at the community level with data privacy protection. Initially, enhanced Transformer neural networks, employing a fused-attention mechanism, are deployed to precisely delineate the solar power generation pattern. Subsequently, federated learning principles facilitate the sharing of specific parameters among multiple edge endpoints and a central server. This model bifurcates into two layers: an individual layer, where parameters are retained locally, and an exchange layer, where parameters are collectively shared and conveyed through momentum aggregation. This dual-layer structure effectively synchronizes the capture of both unique and common characteristics. The test on the Australian residential load dataset verifies the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

In contemporary distribution networks (DNs), characterized by extensive integration of distributed energy, the photovoltaic (PV) power output data from the distribution station areas become crucial for system planning and operational optimization. Since many PVs are installed behind-the-meter (BTM), it is difficult to directly obtain PV power data through measurement devices. Therefore, it is important to estimate the BTM PV power from the aggregating data that can be directly obtained. However, the existing estimation methods usually require centralized large-scale data training, which brings certain privacy leakage risks. In order to solve these problems, we propose a federated learning-based improved Transformer Neural Network strategy to estimate BTM PV generation at the community level with data privacy protection. Initially, enhanced Transformer neural networks, employing a fused-attention mechanism, are deployed to precisely delineate the solar power generation pattern. Subsequently, federated learning principles facilitate the sharing of specific parameters among multiple edge endpoints and a central server. This model bifurcates into two layers: an individual layer, where parameters are retained locally, and an exchange layer, where parameters are collectively shared and conveyed through momentum aggregation. This dual-layer structure effectively synchronizes the capture of both unique and common characteristics. The test on the Australian residential load dataset verifies the effectiveness of the proposed method.

The onboard balise transmission module generates a 27.095 MHz RF carrier wave and transmits it through CAU to the trackside balise. The study and analysis of the control implementation circuit of RF power switch, value and mode of the balise transmission module can deepen the understanding of the design principle of BTM transmission unit and help locate the fault point of insufficient output power, and promote the quality improvement and performance optimization of the balise transmission module. [ABSTRACT FROM AUTHOR]

The reason of the interference problem of BTM system is that it is greatly affected by the external environment and car body working conditions in the process of failure, and it is difficult to find after the fault occurs, and the means are limited, so it is impossible to formulate effective rectification measures. Through analyzing the new CR300BF EMU BTM system fault phenomenon, this paper mainly studies the fault investigation, determination, treatment and summary, finally finds out the cause of the fault after many processing and research, and formulates effective measures, which provides ideas and methods for the acceptance, maintenance and fault treatment of the onboard train control equipment of similar models in the future. [ABSTRACT FROM AUTHOR]

This article, published in the International Journal of Finance, Insurance & Risk Management, analyzes the factors affecting stock returns during the Covid-19 pandemic. The study examines the relationship between Covid cases and stock returns using quantitative methods and secondary data obtained from the IDX. The findings show that daily positive confirmation variables, Covid deaths, and recovery confirmations have a significant negative effect on stock returns, while LMCAP and BTM variables have a significant positive effect. The research highlights the impact of Covid-19 on stock prices, particularly for cyclical stocks or issuers closely tied to economic conditions. [Extracted from the article]

Nowadays, online users write short messages to share their feelings on social networking sites, such as discussion forums, question answering websites, etc., making these sites very popular. The increase in these short-term messages causes a huge data sparsity, making emotion recognition a challenging task. Therefore, a word co-occurrence pattern called biterms is generated from a large-scale dataset to prevent severe data sparsity issues. The topic modeling algorithms and acceleration algorithms are implemented to extract more reliable topics from the group of terms. Based on biterm technique, in this paper, a new algorithm called "Affected biterm emotion topic" is proposed for emotion recognition from a short text. For the experimental purpose, two popular short text datasets, SemEval and International Survey on Emotion Antecedents and Reactions (ISEAR), are used to investigate the performance of the proposed algorithm with the benchmark methods light latent dirichlet allocation (LLDA), biterm topic model (BTM), emotion-topic model (ETM), contextual sentiment topic model (CSTM), Sentiment latent topic model (SLTM) and siasme network based supervised topic model (SNSTM). The proposed algorithm is evaluated using the benchmark methods for mean, variance, and accuracy. The experimental result shows that the proposed algorithm is effective in analyzing emotions. [ABSTRACT FROM AUTHOR]

Reinforced concrete (RC) core walls are commonly used to provide buildings with lateral and torsional resistance against the actions of wind and earthquakes. In low-to-moderate seismic regions, it is not unusual to find a single peripheral core wall that alone should resist these actions, where the torsional (rotational) twist cannot be neglected. It has previously been difficult to have confidence in simulating the axial-flexure-torsion behavior of these RC core walls, primarily due to: (i) some types of modelling approaches being unable to appropriately account for the shear-flexural action, as well as torsional response; and (ii) the scarcity of experimental data, particularly for walls under torsional loads, which would be required to validate such models. In this research, beam-truss models (BTMs), which correspond to an interesting compromise between detailed modelling and practical applications, were used to simulate the in-plane and diagonal flexural response of RC U-shaped walls. Furthermore, the global torque-rotation results from a recent experimental wall test provided the evidence to further validate this powerful modelling technique. A case study building, comprising an RC U-shaped core wall structure with varying eccentricity values, was evaluated for an earthquake event with a 2475-year return period in the city of Melbourne, Australia, using the capacity spectrum method. Nonlinear static pushover analyses showed that, depending on the magnitude of torsion, the in-plane flexural strength and displacement capacity can be significantly reduced. The results from this research emphasize the importance of including torsional actions in the design and assessment of reinforced concrete buildings.

Objective: NovoSorb (Poly-Novo Ltd, Australia) biodegradable temporising matrix (BTM) is a novel artificial dermal matrix. Previous literature is weighted towards its use in burns reconstruction; however, this paper describes its use within a range of wound aetiologies. The authors present one of the largest and most diverse case series to date, and aim to provide an independent benchmark of clinical practice. Method: A retrospective observational study was performed. Patient demographics and clinical data (wound aetiology, site, total body surface area (TBSA), wound bed, number of debridements, time to BTM integration, time to skin grafting) were collected and subgroup analysis preformed. Results: The cohort consisted of 37 patients (acute trauma wounds, n=19; hard-to-heal wounds, n=9; acute infections, n=6; cancer, n=3). Successful BTM integration, allowing subsequent split-thickness skin grafting (STSG), occurred in 70% of cases, despite an overall complication rate of 51%. Mean time from BTM application to STSG was 53 days. There was no difference in STSG outcomes when grafting was performed either before or after the six-week BTM application period. There was no difference when various wound beds (fascia, tendon, periosteum) were compared. Patients >65 years of age were more likely to experience complications; however, this did not affect the speed of integration. The relation of diabetes and smoking to overall integration had no statistical significance. Conclusion: In comorbid patients in particular, the time between BTM application and STSG may be longer than the manufacturer's recommendation. Furthermore, data suggest greater wound bed optimisation and closer interval monitoring in hard-to-heal/malignant wounds, and in older patients and patients with comorbidities. However, BTM appears robust (even in infection) and is showing promise as a useful reconstructive tool. Declaration of interest: The authors confirm that there are no study sponsors. The authors have no conflicts of interest. [ABSTRACT FROM AUTHOR]

Nowadays, Study of comments in MicroBlog online public opinion is of great significance for relevant departments in managing public opinion, due to the increasing influence of online public opinion on the Internet. This paper presents a method for studying the evolutionary characteristics of netizens’ comment focus in university online public opinion. This method is based on a three-stage framework called Topic-Temporal-Focus. Firstly, in the topic mining stage, the KTF-BTM model is proposed for topic recognition, which effectively improves the quality of analysis. Secondly, in the temporal segmentation stage, time periods are divided into 4-hour intervals, and the identified topics are paired with each comment text to generate a topic-temporal list. Finally, in the focus recognition stage, the content and evolution patterns of netizens’ comment focus within shorter time sequences are explored by analyzing the data characteristics of the topic-temporal list. Experimental results show that the proposed KTF-BTM model significantly enhances topic recognition quality for short texts. The Topic-Temporal-Focus framework overcomes the challenge of sparse comment text data within shorter time periods and effectively classifies topic evolution within limited time sequences. This research work serves as a valuable contribution towards understanding the evolutionary characteristics of netizens’ focal points in university online public opinion.

Reinforced concrete (RC) core walls are commonly used to provide buildings with lateral and torsional resistance against the actions of wind and earthquakes. In low-to-moderate seismic regions, it is not unusual to find a single peripheral core wall that alone should resist these actions, where the torsional (rotational) twist cannot be neglected. It has previously been difficult to have confidence in simulating the axial-flexure-torsion behavior of these RC core walls, primarily due to: (i) some types of modelling approaches being unable to appropriately account for the shear-flexural action, as well as torsional response; and (ii) the scarcity of experimental data, particularly for walls under torsional loads, which would be required to validate such models. In this research, beam-truss models (BTMs), which correspond to an interesting compromise between detailed modelling and practical applications, were used to simulate the in-plane and diagonal flexural response of RC U-shaped walls. Furthermore, the global torque-rotation results from a recent experimental wall test provided the evidence to further validate this powerful modelling technique. A case study building, comprising an RC U-shaped core wall structure with varying eccentricity values, was evaluated for an earthquake event with a 2475-year return period in the city of Melbourne, Australia, using the capacity spectrum method. Nonlinear static pushover analyses showed that, depending on the magnitude of torsion, the in-plane flexural strength and displacement capacity can be significantly reduced. The results from this research emphasize the importance of including torsional actions in the design and assessment of reinforced concrete buildings. [ABSTRACT FROM AUTHOR]

Background: In patients with type 1 diabetes mellitus (T1DM), accelerated bones turnover and bone loss are caused by increased inflammation. The serum levels of the bones turnover markers (BTM), serum procollagen type 1 N-terminal propeptide (P1NP) and serum C-terminal telopeptide of type I collagen (CTX), can help identify increasing bones fragility in T1DM earlier on. Objective: The aim of the study is to measure the levels of BTM in children with T1DM, specifically serum P1NP and serum CTX, and to look into the relationships between BTM and indicators of glycemic control and diabetics micro-vascular problems. Patients and Methods: A total of 40 pediatric and adolescent T1DM children were compared with a control group of healthy control, age- and sex-matched participants. HbA1c, fasting lipids profiles, microalbumin in urine, fasting serum P1NP, and serum CTX concentrations were measured in the laboratory. Results: P1NP and CTX concentrations in the sick group were statistically significantly higher than those in the control group (p<0.001), according to the findings of our research. LDL-C and TDD of insulin, which rose in the uncontrolled sample, were determined to differ significantly between participants with HbA1c =7% and participants with HbA1c =7% (p<0.001 and p=0.008, respectively), although there was no differences in the levels of serum P1NP and CTX between the two samples. Conclusion: In younger T1DM children, serum concentrations of P1NP and CTX may offer predictive information on bones health. To demonstrate that oxidative stress causes major changes in the activities of bone production and resorption, more research should be conducted. [ABSTRACT FROM AUTHOR]

Complex and chronic wounds represent a highly prevalent condition worldwide that requires a multimodal and interdisciplinary treatment approach to achieve good functional and aesthetic outcomes. Due to increasing costs of health care, an aging population and an increase in difficult-to-treat microbial colonization of wounds, complex wounds will become a substantial clinical, social and economic challenge in the upcoming years. In plastic reconstructive surgery, a variety of dermal skin substitutes have been established for clinical use. Since its approval as a dermal skin substitute in Germany, NovoSorb® Biodegradable Temporising Matrix (BTM) has become a valuable therapeutic option for the treatment of full-thickness wound defects. The clinical data published to date are limited to case reports and small-scale case series with the main focus on single wounds. The aim of this single-center study was a retrospective analysis of our own patient collective that has received treatment with BTM for complex wounds. Overall, BTM showed to be a reliable and versatile reconstructive option, especially for patients with multiple co-morbidities and microbiologically colonized wounds. Although the preliminary findings have produced promising results, further investigation and research are warranted regarding long-term outcomes and additional clinical applications. [ABSTRACT FROM AUTHOR]

The objective of this systematic review and meta-analysis is to assess the efficacy of the biodegradable temporising matrix (BTM) (NovoSorb; PolyNovo Biomaterials Pty Ltd, Port Melbourne, Victoria, Australia) in the reconstruction of complex upper extremity wounds. The authors conducted a systematic review and meta-analysis as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines assessing the efficacy of BTM in complex upper extremity wound reconstruction. The primary outcome measures were successful BTM integration and the proportion of wounds healed. Secondary outcomes analysed were the average time from BTM application to its integration, the proportion of wounds healed by secondary intention, graft take over BTM, as well as the incidence of infection. The rate of complications as well as scarring and outcomes in upper limb function were also evaluated. The inclusion criteria were met by 12 studies consisting of 164 complex upper extremity wounds. Successful BTM integration was reported in 92.1% (p<0.001) of cases, coupled with wound healing achieved in 90% (p<0.001) of cases overall. The average time to integration for BTM was 37.37 days (p<0.001). The average infection rate for upper extremity wounds with BTM application was 8.5% (p<0.001). Satisfactory scarring and functional outcomes were reported in the majority of the studies. The authors conclude that BTM offers good wound healing outcomes for upper extremity reconstruction. The studies analysed indicate good graft take rates and a low infection incidence; however, further prospective randomised studies are required to support the efficacy of BTM compared to other dermal matrices., Competing Interests: Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Kostova et al.)

This study aimed to analyze the moderating role of Information Technology in the performance of Baitut Tamwil Muhammadiyah(BTM)in Central Java, Indonesia. The target population was members of this Islamic Microfinance Institution. Data from 2015 to 2018 in the Central Java Sharia Office was used to obtain a sample size of 14 from 21 BTMs. Multiple Regression Analysis was then applied to analyze this data and explain the relationship between variables. The results showed that independent variables, including CAR, NPF, and BOPO ratios are positively correlated with ROA (Return on Assets) of BTM, except FDR. Information technology system moderation variables including FDR_SYSTEM and BOPO_SYSTEM significantly and positively affect ROA, while CAR_SYSTEM and NPF_SYSTEM are negatively correlated with the returns on total assets of the institution. In general, BTM should use I.T. for excellent performance and join academics and other stakeholders to increase awareness of the benefits of these computer-based systemsin Islamic Microfinance institutions

Large burns generate significant hypermetabolic and inflammatory responses which increase cardiovascular complications in animal models. A 70 year old male (Fig. 1a) presented with 20% total body surface area flame burns, involving his anterior chest wall. His burn wounds were debrided and temporised with a dermal substitute [NovoSorb® Biodegradable Temporising Matrix (BTM)]. His post-operative course was complicated by acute coronary syndrome requiring coronary artery bypass grafting via sternotomy through the BTM integrating into the chest wall wounds. The patient proceeded to complete BTM integration despite the sternotomy incision carried out through it, with excellent graft take and uncomplicated healing. We describe a previously unreported application of BTM for burn wound reconstruction using a technique that facilitated a surgical incision to carry out open cardiac surgery without compromising wound healing.

Copyright of Gazi University Journal of Gazi Educational Faculty (GUJGEF) is the property of Gazi University Journal of Gazi Educational Faculty (GUJGEF) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Railway Signalling & Communication Engineering is the property of Railway Signalling & Communication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Novel treatments for extensive full-thickness burns revolve around fluid control, addressing systemic inflammatory derangements, and achieving early skin coverage with acceptable cosmetic and functional results. Recent advances in the management of extensive burns include fish skin xenografts, such as Kerecis Omega-3 acellular dermal substitute. Reported to be non-allergenic and antimicrobial, this Atlantic Cod skin derivative has the potential to supplement the management of patients with large surface area burns. A chart review was performed on two complex patients. Patient 1 suffered 65% partial and full-thickness burns after lighting herself on fire with gasoline, and patient 2 suffered 86% partial and full-thickness burns following a methamphetamine explosion. The patients were both treated with a multi-step process using cadaveric allografts, Kerecis acellular fish skin placement, and autologous split-thickness skin grafts (STSG). Case 2 utilized ReCell autologous skin cell suspension and Novosorb bilaminate dermal substitute (BTM TM ) due to limited donor sites. Complete coverage and epithelization were achieved on both patients but required multiple reapplications of autograft and Kerecis. Contractures of the neck, elbows, and hand were present in Case 1. Kerecis xenografting may have an expanding role in burn management due to standalone capabilities for deep partial-thickness burns and ease of use. Further evaluation is needed to establish the most optimal timing of use and best zones of application to improve take and reduce contractures., Competing Interests: Human subjects: Consent was obtained or waived by all participants in this study. Arrowhead Regional Medical Center Institutional Review Board (IRB) issued approval IRB #21-27. Conflicts of interest: In compliance with the ICMJE uniform disclosure form, all authors declare the following: Payment/services info: All authors have declared that no financial support was received from any organization for the submitted work. Financial relationships: All authors have declared that they have no financial relationships at present or within the previous three years with any organizations that might have an interest in the submitted work. Other relationships: All authors have declared that there are no other relationships or activities that could appear to have influenced the submitted work., (Copyright © 2024, Cerceo et al.)

Copyright of Railway Signalling & Communication Engineering is the property of Railway Signalling & Communication Engineering and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The history of the use of computer and data driven technologies by the railways is largely unknown and is very much overshadowed by a deep fascination with the steam railway. However, it was a willingness to embrace and develop these technologies that laid the foundations for the railway that we have today. This paper aims to show the history of the railway’s ‘long engagement’ with these forms of communication and control technologies. This history forms the background to the increasing adoption of internet-based technology on today’s railway, and thus provides a thread connecting the past, present and future of the rail system. A central argument here is that railway management of necessity focuses on control to ensure the safe operation and efficient running of trains and the management of a large and scattered workforce.[1] Control of revenue and costs, including wages and pensions,[2] as well as control of trains on heavily used lines, generated the need for control of data from an early stage. Consequently, UK railways were pioneer adopters of a succession of control technologies including the electric telegraph, ‘Hollerith’ tabulating machines and digital computers.

Natural disasters have caused substantial economic losses and numerous casualties. The demand analysis of relief supplies is the premise and basis for efficient relief operations after disasters. With the widespread use of social media, it has become a vital channel for people to report their demand for relief supplies and provides a way to obtain information on disaster areas. Therefore, we present a topic model-based framework and establish a demand dictionary and a gazetteer that aims to identify the spatial distribution of the demand for relief supplies by using social media data. Taking the 2013 Typhoon Haiyan (also called Yolanda) as a case study, we identify the potential topics of tweets with the biterm topic model, screen the tweets related to demands, and obtain the demand and location information from tweets to study the distribution of the relief supplies needs. The results show that, based on the demand dictionary, a gazetteer and the biterm topic model, the effective demand for relief supplies can be extracted from tweets. The proposed framework is feasible for the identification of accurate demand information and its distribution. Further, this framework can be applied to other types of disaster responses and can facilitate relief operations. [ABSTRACT FROM AUTHOR]

The history of the use of computer and data driven technologies by the railways is largely unknown and is very much overshadowed by a deep fascination with the steam railway. However, it was a willingness to embrace and develop these technologies that laid the foundations for the railway that we have today. This paper aims to show the history of the railway's 'long engagement' with these forms of communication and control technologies. This history forms the background to the increasing adoption of internet-based technology on today's railway, and thus provides a thread connecting the past, present and future of the rail system. A central argument here is that railway management of necessity focuses on control to ensure the safe operation and efficient running of trains and the management of a large and scattered workforce.[1] Control of revenue and costs, including wages and pensions,[2] as well as control of trains on heavily used lines, generated the need for control of data from an early stage. Consequently, UK railways were pioneer adopters of a succession of control technologies including the electric telegraph, 'Hollerith' tabulating machines and digital computers. [ABSTRACT FROM AUTHOR]

Microblog hot topic discovery is one of the research hotspots in the field of text mining. The distance function of traditional K-means leads to low clustering accuracy, which leads to poor hot topic discovery. Three definitions are proposed in this paper: title words and body words, positional contribution-based weight and fusion similarity-based distance. The short text clustering algorithm based on BTM and GloVe similarity linear fusion (BG & SLF-Kmeans) is further proposed. BTM and GloVe are used to model the preprocessed microblog short texts. JS divergence is adopted to calculate the text similarity based on BTM topic modeling. WMD of improved word weight (IWMD) is used to calculate the text similarity based on GloVe word vector modeling. Finally, the two similarities are linearly fused and used as the distance function to realize K-means clustering. Specific word sets of 6 hot topics can be obtained, and microblog hot topics can be discovered. The experimental results show that BG & SLF-Kmeans significantly improves clustering accuracy compared with TF-IDF & K-means, BTM & K-means, and BTF & SLF-Kmeans.

Fawaz Y Azizieh,1 Diaa Shehab,2 Khaled Al Jarallah,2 Olusegun Mojiminiyi,3 Renu Gupta,4 Raj Raghupathy51Department of Mathematics and Natural Sciences, International Centre for Applied Mathematics and Computational Bioengineering, Gulf University for Science and Technology, Kuwait City, Kuwait; 2Department of Medicine, Faculty of Medicine, Kuwait University, Kuwait City, Kuwait; 3Department of Pathology, Faculty of Medicine, Kuwait University, Kuwait City, Kuwait; 4Department of Radiology, Faculty of Medicine, Kuwait University, Kuwait City, Kuwait; 5Department of Microbiology, Faculty of Medicine, Kuwait University, Kuwait City, KuwaitObjective: In addition to some well-characterized bone turnover markers (BTMs), cytokines and adipokines have also been suggested to be linked to osteoporosis seen in menopause. However, there is much controversy on the possible association between these markers and bone mineral density (BMD). This study was aimed at measuring circulatory levels of selected cytokines, adipokines and BTMs in postmenopausal women with normal and low BMD.Methods: The study population included 71 post-menopausal women, of whom 25 had normal BMD, 31 had osteopenia and 13 had osteoporosis. Circulatory levels of selected pro-resorptive (TNF-α, IL-1β, IL-6, IL-8, IL-12, IL-17), anti-resorptive (IFN-γ, IL-4, IL-10, IL-13, TGF-β) and five adipokine markers (adiponectin, adipsin, lipocalin-2/NGAL, PAI-1 and resistin) were measured using the Multiplex system and read on the Magpix ELISA platform. Further, two bone turnover markers (PINP, CTX) as well as estradiol levels were assayed from the same samples.Results: While circulatory levels of cytokines were comparable between groups, women with low BMD had statistically significantly higher median circulatory levels of adipokines as compared to those with normal BMD. Further, while levels of CTX were not different between the two groups; PINP, PINP/CTX ratio and estradiol levels were significantly lower in women with low BMD. Levels of adiponectin, PINP, PINP/CTX ratio and estradiol correlated significantly with BMD of the hip and spine.Conclusion: The associations between various markers and BMD are complex and multivariate. Our data provide insights into the possible use of circulatory levels of cytokines, adipokines and bone turnover markers on the pathogenesis of postmenopausal osteoporosis because of the well-documented effects of these molecules on bone tissue and their relevance to osteoporosis.Keywords: cytokines, adipokines, BTM, osteoporosis, menopause

As one of the fundamental information extraction methods, topic model has been widely used in text clustering, information recommendation and other text analysis tasks. Conventional topic models mainly utilize word co-occurrence information in texts for topic inference. However, it is usually hard to extract a group of words that are semantically coherent and have competent representation ability when the models applied into short texts. It is because the feature space of the short texts is too sparse to provide enough co-occurrence information for topic inference. The continuous development of word embeddings brings new representation of words and more effective measurement of word semantic similarity from concept perspective. In this study, we first mine word co-occurrence patterns (i.e., biterms) from short text corpus and then calculate biterm frequency and semantic similarity between its two words. The result shows that a biterm with higher frequency or semantic similarity usually has more similar words in the corpus. Based on the result, we develop a novel probabilistic topic model, named Noise Biterm Topic Model with Word Embeddings (NBTMWE). NBTMWE extends the Biterm Topic Model (BTM) by introducing a noise topic with prior knowledge of frequency and semantic similarity of biterm. NBTMWE shows the following advantages compared with BTM: (1) It can distinguish meaningful latent topics from a noise topic which consists of some common-used words that appear in many texts of the dataset; (2) It can promote a biterm's semantically related words to the same topic during the sampling process via generalized P ó l y a Urn (GPU) model. Using auxiliary word embeddings trained from a large scale of corpus, we report the results testing on two short text datasets (i.e., Sina Weibo and Web Snippets). Quantitatively, NBTMWE outperforms the state-of-the-art models in terms of coherence, topic word similarity and classification accuracy. Qualitatively, each of the topics generated by NBTMWE contains more semantically similar words and shows superior intelligibility. [ABSTRACT FROM AUTHOR]

For high-speed train, balise transmission module (BTM) system is easily interfered with by other equipment of the train. This could cause the train to malfunction. Studying the electromagnetic susceptibility (EMS) of the BTM is very important for the performance and efficiency of the train. In this paper, a modular, system-level modeling method is proposed to predict the EMS of BTM systems. Based on object-oriented technology and a modular method, the BTM system is disassembled into several modules according to the electromagnetic characteristics of the whole system rather than the physical structure. All the modules are mutually independent, and the total EMS could be evaluated by the output of them. The modules of three key elements of electromagnetic compatibility (EMC), i.e., sources, coupling paths, and sensitive equipment, are established by the theoretical method, full-wave simulation method, and black-box test method, respectively, and put into different layers. According to the functions of the BTM system, the EMS of BTM is given by analyzing the interrelation of input and output of modules. Results of the proposed model were verified by measurement. [ABSTRACT FROM AUTHOR]

NovoSorbⓇ Biodegradable Temporising Matrix (BTM) is a synthetic dermal template recently approved for treatment of full thickness defects of the skin. It requires a two-stage reconstruction where it is initially placed into a defect to generate a neodermis, which is later covered by a split skin graft. It has previously been described for the treatment of acute full thickness burn injury, necrotising fasciitis and free flap donor site reconstruction. A consecutive case series review of patients treated with BTM at Middlemore Hospital was performed. Patient demographics, defect aetiology, indications for dermal matrix use, surgical details, and complications were recorded using information gathered from the medical records. This case series included 25 patients with a range of defects resulting from acute full thickness burn injury, burn scar revision, necrotising soft-tissue infection, tumour excision and traumatic loss. In these patients, 72% of wounds were identified as complex defects with exposed bone or tendon. Complications encountered included infection, non-adherence and incomplete vascularisation. BTM provided a good reconstructive option for a wide range of defects, many of which were not amenable to immediate skin grafting. Once vascularised and ready for the second stage, it developed a red-pink colour and demonstrated capillary refill. Similar to other dermal matrices, infection was a commonly encountered problem. However, BTM proved more tolerant to this and was able to be salvaged in most cases, allowing the second stage to proceed as normal. [ABSTRACT FROM AUTHOR]

Copyright of Journal of East China University of Science & Technology is the property of Journal of East China University of Science & Technology Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This is a proposal to encode the Batak script in the international character encoding standard Unicode. This script was published in Unicode Standard version 6.0 in October 2010. Batak is used to write five Batak dialects that are spoken on the island of Sumatra: Karo, Mandailing, Pakpak, Simalungun, and Toba.

Summary: Bone formation markers bone-specific alkaline phosphatase and osteocalcin are used in many clinical situations. Therefore, we calculated reference intervals for the two markers and investigated how they are influenced by several factors including sex and age. Furthermore, we established clinically relevant reference intervals for the two markers. Objective: The bone turnover markers (BTMs), bone-specific alkaline phosphatase (bone ALP), and osteocalcin (OC), are frequently measured formation markers. The purpose of this study was to establish reference intervals (RIs) for the two BTMs in a general adult Danish population. Methods: Bone ALP and OC were measured on the iSYS (IDS Plc) automatic analyzer in samples from the Danish Health2006 5-year follow-up study on serum from 2308 participants (54% women, age range 24–76). Participants with self-reported diagnosis of osteoporosis or receiving hormonal replacement were excluded from analyses while participants on hormonal contraceptives were included. Results: The geometric mean and 95%RI for bone ALP were 13.9 μg/L (7.6–25.6) for men and 13.8 μg/L (7.0–27.4) for women, while for OC 16.0 μg/L (7.5–34.4) for men and 18.6 μg/L (8.1–42.9) for women. Levels of bone ALP increased with increasing age (β 1.004, p < 0.001), while female sex had no effect. OC levels decreased with increasing age (β 0.998, p = 0.009) and increased with female sex (β 1.104, p < 0.001). Based on our findings, we propose for bone ALP and OC three clinical RIs for men based on age and three clinical RI for women based on age and menopausal status. Conclusion: The RI for bone ALP and OC varies with age and sex and the BTMs are influenced differently by the two factors. Consequently, the need for establishing valid RIs is of great importance before the full potential of BTM can be used in clinical practice. [ABSTRACT FROM AUTHOR]

Microblogs have a large amount of data but a few characters in the text, and their features are sparse. In order to improve the retrieval precision, we propose a microblog retrieval model combining BTM and graph theory. The lexical semantic correlation is used to calculate the correlation between features with labels in microblog text. Then we construct a bi-term topic model，use JSD distance to calculate the correlation of pair words in the short text that mapped to the model. Thirdly，we extract the entity and graph structure in CN-DBpedia，and then use the SimRank algorithm to calculate inter-entity correlation between graph structures. The above three correlations are the final correlation of the model. Finally，the Sina Weibo data set is used for the retrieval experiments. Experimental results show that compared with the retrieval model based on the combination of the implicit Dirichlet distribution algorithm and graph theory and the system model based on open data correlation and graph theory, the performance of the new model is significantly improved in MAP, accuracy and recall rate, indicating that the model has better retrieval performance. [ABSTRACT FROM AUTHOR]