Core Problem Research Articles

Dengue Outbreak Control and Prevention: A Case Study of Gampaha District, Sri Lanka

Dengue fever remains a persistent public health challenge in Gampaha District, Sri Lanka. Despite ongoing efforts by the Ministry of Healthcare, Nutrition & Indigenous Medicine, the district reported 10,212 cases in 2022, with significant hospital admissions and deaths in high-risk areas like MC Negombo, Gampaha, and Minuwangoda. The study examines Dengue control and prevention strategies implemented from November 2022 to March 2023. Data was collected from existing records, interviews with key informants, and field observations. Major challenges were identified and prioritised using evidence-based methodologies, including the "Five Whys" root cause analysis. The analysis revealed significant challenges categorised into program-related and non-program-related issues. Key issues include inadequate use of existing data, insufficient evidence-based control measures, and operational inefficiencies. The root cause analysis identified core problems such as lack of funding, poor planning, and limited community engagement. The study highlights the critical need for data-driven decision-making and enhanced collaborative efforts. Establishing a technical body, develop context-specific programs, and improve community involvement. Resource mobilisation for research and forecasting epidemics was also emphasised. This case study provides valuable insights into the challenges and strategic interventions necessary for effective Dengue control in the Gampaha District. Emphasising evidence-based decision-making and a comprehensive action plan underscores the importance of collaborative efforts to combat Dengue in the region.

Utilization of home-based care and its buffering effects between dementia caregiving intensity and caregiver burden in China.

Home-based care (HBC) services have gained global attention for their potential to reduce caregiver burden among informal caregivers of persons with dementia (PwDs), who experience high caregiving intensity. However, research on HBC and its effects on dementia caregiving in China remains limited. Data were collected from primary caregivers of PwDs in Jiangsu Province, China. Caregiving intensity and HBC utilization were measured using self-developed instruments. Caregiver burden was assessed by The Burden Scale for Family Caregivers-short. Factor analysis was employed to decompose HBC services. Hierarchical multiple regression analysed the moderating effects of HBC on the relationship between caregiving intensity and burden. A community sample of 318 caregiver and PwDs dyads was included. Caregivers averagely aged 62.16 years, with 61% being female, 84% not employed, and 66.2% having low income. PwDs aged 77.45 years averagely, with 52.8% being female and an average behavioural problems score of 42.27. Caregivers averaged 15.19 on response measures. The number and time spent on ADL-based tasks were positively associated with caregiver burden (β = 0.26, p < .001; β = 0.16, p < .01). However, attendance and time of supervision tasks were not significant predictors of burden. HBC services in China comprised four dimensions: Referral service, Household care, Skilled care, and Mental health service. While these did not directly predict caregiver burden, they moderated the associations between ADL-based tasks and caregiver burden (β=-0.25, p < .001; β=-0.24, p < .001; β=-0.23, p < .001; β=-0.20, p < .001), between time of ADL-based tasks and caregiver burden (β=-0.17, p < .001; β=-0.18, p < .001; β=-0.17, p < .001; β=-0.15, p < .01), and between the attendance at supervision tasks and caregiver burden (β=-0.11, p < .05; β=-0.20, p < .001; β=-0.17, p < .001; β=-0.17, p < .001). Only Referral service buffered the relationship between supervision time and caregiver burden (β = -0.13, p < .01). Informal caregivers of PwDs face high caregiving intensity and burden. HBC services may moderate this relationship, with different services playing varying roles. Further research is essential to explore the impact of supervision levels and develop effective strategies to enhance HBC services for dementia caregiving in China.

Rates of socio-emotional difficulties among deaf and hard of hearing children in Ireland

ABSTRACT Higher rates of socio-emotional difficulties for deaf and hard of hearing (DHH) children have been reported compared with their typical hearing (TH) peers. Nonetheless, there has to date been limited examination on this issue internationally and no such examination in the Republic of Ireland. In this study, data was collected from parents using an online survey which included the Strengths and Difficulties Questionnaire to examine the socio-emotional development of 113 DHH children aged 5–16 in the Republic of Ireland. The results were compared with data from typically hearing (TH) children obtained from a large longitudinal study of childhood in Ireland – the Growing Up in Ireland study. The findings demonstrate that the prevalence of socio-emotional difficulties among this cohort of children is over three times that of the general population of children in Ireland, with 42% of the sample demonstrating clinically significant problem scores. Furthermore, DHH children had elevated subscale scores for the four problem scales in the SDQ when compared against the TH sample. These differences were statistically significant and had a range of effect sizes from small to large. The subscale of most concern was the peer problems subscale where the DHH sample had mean scores that were roughly double those of the TH sample, with a large effect size found. Finally, bivariate analysis revealed that several background variables were associated with elevated difficulty scores for DHH children, namely male gender, poorer communicative competency, and presence of an additional educational need.

Against decolonial reductionism: The impact of Latin American thinking on the data decolonization project

This essay argues that Latin American scholarship and movement practice are key to understanding the dynamics of the datafied society and countering its inequities. Examining the sources of inspiration of a frontrunner seeking to decolonize the datafied society – the Big Data from the South Initiative ( BigDataSur) – we review Martín-Barbero's ontological shift from media to mediations, Freire's methodology centring individual agency and empowerment as a structural task of society, Mignolo's invite to take decoloniality as a praxis rather than merely an idea, Rodríguez's first-hand engagement with technology at the margins, Escobar's autonomous design for the pluriverse, and the critical ecology of eco-social movements. We engage with a new generation of Latin American thinkers who turn their gaze to core problems of today's systems of knowledge production, be they media or academia. Learning from these scholars, we warn against decolonial reductionism, namely the trend to evoke decolonial ideas and theories without fully committing to putting them into practice. We maintain that to decolonize datafication, we ought to also change how we generate knowledge about the datafied society. We outline three practical strategies that foster an open-ended dialogue on alternative approaches to datafication and scientific practice: multilingualism, public scholarship, and mentorship.

Identifying childhood pesticide exposure trajectories and critical window associated with behavioral problems at 10 years of age: Findings from SMBCS

BackgroundPesticides may impact children’s neurodevelopment. As children’s metabolic function and neural plasticity change throughout their growth and development, the effects of pesticide exposure may also vary. ObjectivesWe aimed to identify the trajectories of combined pesticide exposure during childhood, and examine the associations of the exposure trajectories with children’s neurobehavior at the age of 10. MethodsWe involved repeated measurements of three pesticide metabolites [Pentachlorophenol (PCP), 3,5,6-Trichloro-2-pyridinol (TCPy), and Carbofuran phenol (CFP)], in urine samples collected from children in a cohort study at ages 1, 2, 3, 6, 7, 8, 9, and 10 years. The group-based multi-trajectory model (GBMT) and latent class analysis (LCA) were separately utilized to describe the distinct trajectories and patterns of pesticide mixture exposure during childhood. Meanwhile, the Strengths and Difficulties Questionnaire (SDQ) and attention deficit hyperactivity disorder (ADHD) Criteria of Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) list were applied to assess behavioral disorders in children. The associations between exposure trajectories and behavioral problem scores were then examined. ResultsThe GBMT model delineated three distinct trajectories of combined pesticide exposure among children: consistently low, higher levels in early childhood transitioning to lower levels during pre-school age, and lower levels in early childhood followed by higher levels in the middle childhood. The LCA model identified three similar longitudinal exposure patterns. Further, the children in the second trajectory group identified by GBMT, characterized by higher early childhood exposure levels, exhibited significantly elevated hyperactivity/inattention scores of the SDQ compared to the other two groups (β = 0.46, 95 %CI: 0.11, 0.81; β = 0.44, 95 %CI: 0.02, 0.86). ConclusionsOur study revealed that exposure to pesticides during early childhood (especially before the age of two), rather than other age periods, was linked to hyperactivity/inattention problems in children aged 10 years. We also provided a novel perspective on characterizing the fluctuation in repeated measurements of multiple environmental chemicals and identifying the potential critical windows.

Estimated lifetime impact of a school-based intervention for mental health: A microsimulation study

Abstract Background The prevalence of childhood mental health problems is increasing. School-based interventions have the potential to reduce poor mental health and mental health inequalities. Our aim was to estimate the long-term costs and benefits of the Incredible Years Teacher® Classroom Management (IY-TCM) intervention in primary schools compared to no intervention. Methods LifeSim, an existing microsimulation model, was used to estimate the lifetime costs and benefits of IY-TCM by linking short-term changes in SDQ based on a previous trial in primary schools (Cluster RCT: 2075 children aged 4-9 years with a 30-month follow-up) to long-term health, social, economic and wellbeing outcomes. Benefits were measured in quality adjusted life years and wellbeing adjusted life years. We examined subgroup based on deprivation, conduct scores and parental depression. Results Microsimulation modelling estimated small gains in lifetime outcomes including reduced conduct disorder in adolescence and depression in adulthood. Estimates indicate IY-TCM could be cost-effective with a large amount of uncertainty (Net monetary benefit (NMB)=£21, Estimated CI = -£195, £240). IY-TCM was estimated to be more cost-effective for those with high deprivation (NMB = £231, Estimation CI - -£99, £231) and high conduct problem scores (NMB=£315, Estimated CI = £45, £483). Total net social benefit for a typical year size group was estimated to be £111m. Conclusions IY-TCM could be cost-effective compared to no intervention with a large estimated social benefit supporting wider implementation of IY-TCM, but results indicate a large amount of uncertainty. Greater benefits and higher certainty of cost-effectiveness for children with conduct problems and those living in a deprived area suggest IY-TCM has the potential to reduce mental health inequalities and may be more cost-effective for schools with higher deprivation and/or a high prevalence of conduct problems. Key messages • The Incredible Years Teacher Classroom Management intervention for mental health in primary schools could be considered cost-effective but there is a large amount of uncertainty. • Greater benefits for children with conduct problems and those living in a deprived area indicates the intervention has the potential to reduce mental health inequalities.

Associations of fetal and infant growth patterns with behavior and cognitive outcomes in early adolescence

AbstractBackgroundFetal life and infancy might be critical periods for brain development leading to increased risks of neurocognitive disorders and psychopathology later in life. We examined the associations of fetal and infant weight growth patterns and birth characteristics with behavior and cognitive outcomes at the age of 13 years.MethodsPopulation‐based prospective cohort study from fetal life until adolescence. Pregnant women with a delivery date between April 2002 and January 2006 were eligible. Follow‐up measurements were available for 4716 children. Fetal weight was estimated in the second and third trimesters of pregnancy by ultrasonography. Infant weight was measured at birth and at 6, 12, and 24 months. Fetal and infant weight acceleration or deceleration were defined as a change in SD greater than 0.67 between time points. Total, internalizing and externalizing problems and attention‐deficit hyperactivity disorder (ADHD) symptoms were measured using Child Behavior Checklist (CBCL/6–18), autistic traits by the Social Responsiveness Scale (SRS) and intelligence quotient (IQ) by the Wechsler Intelligence Scale for Children‐Fifth Edition (WISC‐V).ResultsOne week longer gestational age at birth was associated with a −0.03 SDS (95% Confidence Interval (CI): −0.04, −0.01) lower total behavior problems score, a −0.02 SDS (95% CI: −0.04, −0.01) lower ADHD symptoms score. Also an increase in birth weight of 500 g was associated with a lower odds of having high externalizing problems (OR 0.92 (95% CI: 0.86, 0.98) and of having a low IQ score (OR 0.79 (95% CI: 0.71, 0.88). Compared to children with normal fetal and infant growth, those with accelerated fetal and infant growth had a 0.27 SDS higher IQ (95% Confidence Interval 0.11, 0.44).ConclusionsBoth fetal and infant weight development are associated with behavioral and cognitive outcomes in early adolescence. Follow‐up studies are needed to assess whether these associations link to later life mental health outcomes.

Revolutionizing bone defect healing: the power of mesenchymal stem cells as seeds.

Bone defects can arise from trauma or pathological factors, resulting in compromised bone integrity and the loss or absence of bone tissue. As we are all aware, repairing bone defects is a core problem in bone tissue engineering. While minor bone defects can self-repair if the periosteum remains intact and normal osteogenesis occurs, significant defects or conditions such as congenital osteogenesis imperfecta present substantial challenges to self-healing. As research on mesenchymal stem cell (MSC) advances, new fields of application have emerged; however, their application in orthopedics remains one of the most established and clinically valuable directions. This review aims to provide a comprehensive overview of the research progress regarding MSCs in the treatment of diverse bone defects. MSCs, as multipotent stem cells, offer significant advantages due to their immunomodulatory properties and ability to undergo osteogenic differentiation. The review will encompass the characteristics of MSCs within the osteogenic microenvironment and summarize the research progress of MSCs in different types of bone defects, ranging from their fundamental characteristics and animal studies to clinical applications.

Language barriers and mental health problems of preschool children born very preterm in Germany.

We assessed whether behavioural and emotional problems of 5- to 6-year-old preschool children born very preterm (<32 weeks' gestation) are associated with an immigrant background and linguistic distance of their first language to the host country's official language, German. This is an observational longitudinal cohort study. Data are from the national multicentre German Neonatal Network cohort, including all very preterm births from 2009 onwards. A total of 3220 (n = 1570 female) children were followed up at preschool age; 629 (n = 324 female) of these had an immigrant background. Behavioural and emotional problems were assessed using the parent-reported Strengths and Difficulties Questionnaire (SDQ). Mixed-effects models showed that immigrant status alone was not associated with children's behavioural and emotional problems. However, a higher linguistic distance of the children's first language to German was associated with higher SDQ total problem scores (coefficient = 0.008, 95% confidence interval 0.002, 0.015), after adjusting for known confounders. Language barriers in the form of linguistic distance between the first language of children born very preterm and countries' official languages are associated with increased risk for behavioural and emotional problems. More research is needed on how language barriers affect long-term developmental outcomes of immigrant children born very preterm.

Between-area communication through the lens of within-area neuronal dynamics.

A core problem in systems and circuits neuroscience is deciphering the origin of shared dynamics in neuronal activity: Do they emerge through local network interactions, or are they inherited from external sources? We explore this question with large-scale networks of spatially ordered spiking neuron models where a downstream network receives input from an upstream sender network. We show that linear measures of the communication between the sender and receiver networks can discriminate between emergent or inherited population dynamics. A match in the dimensionality of the sender and receiver population activities promotes faithful communication. In contrast, a nonlinear mapping between the sender to receiver activity, for example, through downstream emergent population-wide fluctuations, can impair linear communication. Our work exposes the benefits and limitations of linear measures when analyzing between-area communication in circuits with rich population-wide neuronal dynamics.

Advancements to generalized equivalence theory for preserving cross-sections of whole core simulations

The conventional two-step approach, without the use of an equivalence method, can introduce significant error for the simulation of non-LWRs (Light Water Reactors), especially fast reactors, due to the large leakage and high anisotropic neutron distribution. To improve upon the accuracy of the two-step approach, a 3D whole core model is simulated with a transport method to generate region-wise homogenized cross-sections (XS). These XS can then be used in a diffusion whole core solver during the second step to extend the application to cycle and transient analysis. Discontinuity factors (DFs) are then introduced to improve the accuracy during the simulation of the second step. With properly generated DFs from Generalized Equivalence Theory (GET), the region-averaged solutions from the first transport step can then be reproduced by the second step diffusion solver. The Monte Carlo method was selected to perform the whole core transport simulation to generate region-wise XS. However, simulating whole core problems with Monte Carlo may result in poor statistics near the peripheral region especially for partial current tallies. This paper introduces an advancement to GET to reproduce region-wise solutions for select regions when the reaction rates and surface currents have good statistics in these regions but poor statistics in other regions. A reference high-fidelity model was constructed using the Serpent 2 Monte Carlo code based on the EBR-II benchmark evaluation and verification was carried out using the TriPEN-4 method in PARCS. The results show that it is possible to reproduce the exact eigenvalue and power distributions of whole core problems in a feasible manner.

Prediction of shear capacity of RC columns and discussion on shear contribution via the explainable machine learning

The research goal of this paper is to establish a machine learning (ML) model of shear capacity of reinforced concrete (RC) columns that can reflect the shear mechanism. The main work includes building database, training ML model, and interpretability analysis of optimal model. Aiming at the core problem of interpretability of ML methods, this paper proposes an interpretability method for the shear mechanism of RC columns. An experimental database including 427 sets of results of tests on RC columns is established, and eight salient input features are discerned through both mechanical mechanism assessment and Pearson correlation analysis. Twelve models, consisting of six basic ML models and six ensemble ML models, are verified against the database. The assessment reviews that the Light Gradient Boosting Machine (LightGBM) model was demonstrated to be superior to other models, achieving R2 values of 0.999 and 0.987 in training and test sets respectively. Additionally, compared to five semi-empirical models, the results from the LightGBM model also provides more accurate predictions and adeptly considered the influence of parameters. The Shapley additive explanation (SHAP) method and the explainable method based on the RC column shear mechanism proposed by this paper are used to explain the working mechanism of the LightGBM model. The proposed explanatory method of shear contribution rate is combine the additivity of SHAP value with the additivity of shear component contribution, the proposed explanatory method of shear contribution rate. An evaluation of SHAP feature Importance and SHAP feature dependence revealed that LightGBM aligns closely with the inherent shearing mechanism of the RC column. The shear contribution ratios of the concrete, stirrup, and axial loading in RC columns for the LightGBM model are similar to those predicted based on the semi-empirical models.

Historical Development of Social Work and Social Welfare Services in Ethiopia

Social work in Ethiopia has been influenced by the ideology and political economy of governments in power. To explore the core problems social work and social welfare services have experienced, this research employed a systematic review of literature. Organised social welfare services in Ethiopia is a fairly recent phenomenon beginning with the establishment of the first school of social work in 1959. This school was closed in 1974 and then reopened in 2004. The field experienced other challenges too, including its informal merger with the Department of Sociology during the socialist regime. Since social work in Ethiopia is heavily influenced by the Western curriculum and its professional associations have little ability to professionalise the field, its contribution to improving social welfare services is unsatisfactory. Further, because there is no regulatory body, the associations pursue their commitments only sporadically. This has a negative effect on providing quality social welfare services. The future will be determined by the degree to which social work is professionalised.

Bi-objective Optimization in Role Mining

Role mining is a technique that is used to derive a role-based authorization policy from an existing policy. Given a set of users U , a set of permissions P and a user-permission authorization relation UPA ⊆ U × P , a role mining algorithm seeks to compute a set of roles R , a user-role authorization relation UA ⊆ U × R and a permission-role authorization relation PA ⊆ R × P , such that the composition of UA and PA is close (in some appropriate sense) to UPA . Role mining is therefore a core problem in the specification of role-based authorization policies. Role mining is known to be hard in general and exact solutions are often impossible to obtain, so there exists an extensive literature on variants of the role mining problem that seek to find approximate solutions and algorithms that use heuristics to find reasonable solutions efficiently. In this paper, we first introduce the Generalized Noise Role Mining problem (GNRM) – a generalization of the MinNoise Role Mining problem – which we believe has considerable practical relevance. In particular, GNRM can produce “security-aware” or “availability-aware” solutions. Extending work of Fomin et al., we show that GNRM is fixed parameter tractable, with parameter r + k , where r is the number of roles in the solution and k is the number of discrepancies between UPA and the relation defined by the composition of UA and PA . We further introduce a bi-objective optimization variant of GNRM, where we wish to minimize both r and k subject to upper bounds \(r \le \bar{r} \) and \(k\le \bar{k} \) , where \(\bar{r} \) and \(\bar{k} \) are constants. We show that the Pareto front of this bi-objective optimization problem (BO-GNRM) can be computed in fixed-parameter tractable time with parameter \(\bar{r} +\bar{k} \) . From a practical perspective, a solution to BO-GNRM gives security managers the opportunity to identify a mined policy offering the best trade-off between the number of policy discrepancies and the number of roles. We then report the results of our experimental work using the integer programming solver Gurobi to solve instances of BO-GNRM. Our key findings are that (a) we obtained strong support that Gurobi’s performance is fixed-parameter tractable, (b) our results suggest that our techniques may be useful for role mining in practice, based on our experiments in the context of three well-known real-world authorization policies. We observed that, in many cases, our solver is capable of obtaining optimal solutions when the values of either k or r are small.

Dynamic path finding for multi-load agent pickup and delivery problem

Recently, the Multi-Agent Pickup and Delivery (MAPD) problem has attracted widespread attention from both academia and industry. In the MAPD problem, each task has its pickup and delivery locations, and the agent needs to pick this task up from the pickup location and deliver it to its delivery location. Therefore, existing works consider the MAPD problem as the core problem in industrial scenarios, e.g., logistics warehouse. Note that the agents considered in the MAPD problem are single-load agents that complete tasks one by one. However, many commercial companies have deployed agents with multi-load instead of single-load agents to improve efficiency and reduce costs. The agents with multi-load can complete multiple tasks at once, so existing solutions cannot work well with the MAPD problem for multi-agents. To solve this issue, we investigate a novel problem in this paper, namely the Multi-Load Agent Pickup and Delivery (MLAPD) problem, where the agents with multi-load not only need to complete assigned real-time tasks but also need to avoid conflicts with each other and the goal is to minimize the total cost in the warehouse. To address this novel problem, we develop a task assignment to complete the assignments between multi-load agents and online tasks in real-time and a dynamic path finding problem that enables multi-load agents to move along conflict-free paths. Finally, extensive experiments in two different warehouses examine the effectiveness of our solutions.

Impaired head circumference growth and behavioural problems in childhood: Longitudinal findings from the MINA-Brazil birth cohort.

Previous evidence on the relation between early head circumference (HC) growth and behavioural outcomes in preschoolers has been inconsistent. We aimed to investigate whether HC growth from birth to 5 years of age was related to internalising or externalising behavioural problems at 5 years of age in a sex-specific manner. Among 303 girls and 318 boys from the MINA-Brazil birth cohort, we examined the associations between changes in HC from birth to 5 years of age and internalising and externalising behaviour problem scores at 5 years according to the Strengths and Difficulties Questionnaire for parents. HC values were transformed into sex- and age-specific z-scores (HCZ) using World Health Organisation standards, and the differences between values at 5 years of age and birth were classified into quintiles. We estimated adjusted mean differences with 95% confidence intervals in behavioural problem scores between HCZ change quintiles using multivariable linear regression by sex. To examine nonlinear associations, we included cubic spline terms. Head circumference growth from birth to 5 years of age was inversely and nonlinearly associated with internalising problems in girls. Compared with girls at the lowest quintile of HC growth, those above had an adjusted 1.27 (95% confidence interval 0.28, 2.27) points lower mean internalising problems score. This association was mostly driven by HC growth during the first 2 years. We found no association between HC growth and externalising behaviour in either sex. Impaired HC growth was related to higher mean internalising problem scores at 5 years of age in girls but not in boys. HC growth was not associated with externalising problems.

Batik Scan: Empowering Cultural Heritage Knowledge Through Mobile Innovation

Batik Malaysia, a type of textile art known as Batik originated in Malaysia, especially in the east coast states; Kelantan, Terengganu, and Pahang. The Batik mostly uses features flower motifs and designs instead of living creatures, such as humans and animals. Even though Malaysian wear it every day, they do not have sufficient knowledge about Batik. Besides, there is a limited number of platforms where Malaysian can get access to the information of Batik in the easiest and fastest way. Hence, this study aims to design and develop a mobile app for batik identification by only capturing the motifs and designs using a camera feature. The app, called as batik scanner, provides quick information related to Batik Malaysia. This app is especially suitable for adults, batik lovers, and new learners. The advances in digital technology play an important role in helping people to identify the type of Batik Malaysia. It also can reduce the effort of new learners and Batik lovers to find out information of Batik. To ensure that users will have a good mobile user experience, an understanding of the importance and limitation of the mobile app features and behaviour is necessary. Therefore, the design thinking approach was applied as the development methodology as it provides a solution-based approach to solving problems. User requirements were gathered through interviews followed by defining the core problems. Next, innovative solutions were identified using the brainstorm technique and mind mapping. Once the batik scanner prototype was completed, user testing was carried out with the targeted respondents to refine the solution. An online form also was distributed to evaluate the usability of the prototype. The results of the evaluation indicate that the Batik Scanner need to improve some of the interface designs. The respondents were also satisfied with the functions of managing the information in the Batik Scanner. The study contributes toward understanding users’ needs in creating the solution to the identified problems. It may serve as a guideline for other developers and researchers to develop similar apps or to enhance the features of Batik Scanner to become better and easier for users.

Memerna: Sparse RNA folding including coaxial stacking

Determining RNA secondary structure is a core problem in computational biology. Fast algorithms for predicting secondary structure are fundamental to this task.Department of Biochemistry & Biophysics, University of Rochester Medical Center, Rochester, NY, USA We describe a modified formulation of the Zuker-Stiegler algorithm with coaxial stacking, a stabilising interaction in which the ends of helices in multi-loops are stacked. In particular, optimal coaxial stacking is computed as part of the dynamic programming state, rather than in an inner loop. We introduce a new notion of sparsity, which we call replaceability. Replaceability is a more general condition and applicable in more places than the triangle inequality that is used by previous sparse folding methods. We also introduce non-monotonic candidate lists as an additional sparsification tool. Existing usages of the triangle inequality for sparsification can be thought of as an application of both replaceability and monotonicity together. The modified recurrences along with replaceability allows sparsification to be applied to coaxial stacking as well, which increases the speed of the algorithm. We implemented this algorithm in software we call memerna, which we show to have the fastest exact (non–heuristic) implementation of RNA folding under the complete Turner 2004 model with coaxial stacking, out of several popular RNA folding tools supporting coaxial stacking. We also introduce a new notation for secondary structure which includes coaxial stacking, terminal mismatches, and dangles (CTDs) information. The memerna package 0.1 release is available at https://github.com/Edgeworth/memerna/tree/release/0.1.

Deactivation mechanism of catalyst in long-period experiment of 1,1,2-TCE dehydrochlorination

ABSTRACT VDC, as an important raw material for high barrier material PVDC and lithium-ion battery binder PVDF, had an increasing demand. The catalytic dehydrochlorination of 1,1,2-TCE to generate VDC was a green process route that was expected to replace the heavily polluting sodium hydroxide saponification process in industry. There was a certain research foundation for the catalytic dehydrochlorination of 1,1,2-TCE, among which the core problem was that the catalyst was prone to deactivation. Previous studies had calculated the average molecular structure of the spent catalyst surface species when coconut shell activated carbon was used as the support. In subsequent studies, alumina support had been proven to be a better carrier for dehydrochlorination of 1,1,2-TCE, and the selected catalyst had been used in long-period laboratory experiments. The results indicated that the catalyst life had been significantly improved. In the early stage of the reaction, the activity of the catalyst decreased rapidly. In the first 20 h, the conversion of 1,1,2-TCE decreased from 49.35% to 40.36%. From 21 h to 120 h, the conversion of 1,1,2-TCE decreased from 39.96% to 36.18%, tending to stabilize. After 120 h of reaction, the catalyst was extracted and elemental analysis, FTIR, and GPC characterization were performed on the spent catalyst surface species. The average molecular formula of the carbon deposits was obtained as C96.08H50.29Cl36.53. Compared with coconut shell activated carbon support, under the action of activated alumina support, the route of catalyst carbon deposition had changed, and the sediment was more composed of polyvinylidene chloride components. Under certain conditions, sediment formed a dynamic equilibrium, which explained why the activity of the catalyst gradually stabilized. This study revealed the catalytic mechanism of active alumina supported catalyst and the pathway of carbon deposits generation, which was of great significance for improving the lifespan of improved catalyst.

Air turbine starter remaining useful life prediction for bearing based on an improved temporal convolutional network

The air turbine starter (ATS) is an equipment employed for initiating aircraft engines, in which rolling bearings play a central role. Predicting the remaining useful life (RUL) of rolling bearings constitutes a challenging task within the domain of prognostics and health management (PHM). Improving computational efficiency to predict the RUL of bearings is a core problem addressed in this paper, and thus, this paper introduces the parallel causal convolutional hierarchical dilated temporal convolutional network (HD-TCN). HD-TCN effectively captures long-term temporal dependencies and significantly enhances computational efficiency compared to serial convolutional recurrent neural networks (RNNs). In addition, the introduction of the feature data stacking (FDS) module allows features from different hierarchical levels and dimensions to participate in the prediction task, ensuring both computational efficiency and prediction accuracy. To consolidate the extracted multidimensional features, the network incorporates the matrix multiplication dimensionality reduction transformation (MMDRT) module, which reduces the dimensionality of the data and further improves the computational efficiency as well. The introduction of the MMDRT module resulted in reductions of 43.4% in root mean square error (RMSE). The proposed method achieved reductions in RMSE by 38.3% and 46.4% compared to the transformer and long short-term memory (LSTM) models, respectively. Finally, the effectiveness of the proposed method is validated using the XJTU-SY data set and civil aircraft bearing components RUL prediction test bench bearing data. The results show that the proposed approach can predict the RUL of bearings with high accuracy.