Severe Lack Research Articles

Research on the Current Situation and Sustainable Development Measures for Urban–Rural Water Supply Integration in Yunnan Province, China

Urban–Rural Water supply integration is one of the effective ways to address rural drinking water safety issues. With the rapid economic development and urbanization, the gap between urban and rural water supply has become increasingly evident, and rural areas face severe challenges such as insufficient water sources and substandard water quality. Yunnan Province, due to its unique topography and natural environment, encounters numerous difficulties in promoting the construction and development of urban–rural water supply integration, and there is a severe lack of research specifically focused on sustainable development measures for urban–rural water supply integration in Yunnan Province. In light of this, this paper first reviews the current research status on urban–rural water supply integration both domestically and internationally, pointing out that existing studies mainly focus on optimizing urban water supply systems, addressing rural drinking water safety issues, and exploring water supply management models. It then analyzes the challenges faced by Yunnan Province in advancing urban–rural water supply integration, including limitations in engineering construction, inadequate operation and maintenance, complex and variable water source conditions, and insufficient public awareness of water conservation. In response to these issues, a series of sustainable development measures are proposed, including revitalizing existing assets, enhancing construction planning and quality, promoting water pricing reforms, upgrading the technical system for drinking water safety assurance, and advancing the information technology construction of urban–rural water supply integration, with the aim of providing references and insights for the sustainable development of urban–rural water supply integration in Yunnan Province and other regions.

A frameshift mutation in the murine Prkra gene exhibits cerebellar abnormality and reduced eIF2α phosphorylation.

Mutations in Prkra gene, which encodes PACT/RAX cause early onset primary dystonia DYT-PRKRA, a movement disorder that disrupts coordinated muscle movements. PACT/RAX activates protein kinase R (PKR, aka EIF2AK2) by a direct interaction in response to cellular stressors to mediate phosphorylation of the α subunit of the eukaryotic translation initiation factor 2 (eIF2α). Mice homozygous for a naturally arisen, recessively inherited frameshift mutation, Prkralear-5J exhibit progressive dystonia. In the present study, we investigate the biochemical and developmental consequences of the Prkralear-5J mutation. Our results indicate that the truncated PACT/RAX protein retains its ability to interact with PKR, however, it inhibits PKR activation. Furthermore, mice homozygous for the mutation have abnormalities in the cerebellar development as well as a severe lack of dendritic arborization of Purkinje neurons. Additionally, reduced eIF2α phosphorylation is noted in the cerebellums and Purkinje neurons of the homozygous Prkralear-5J mice. These results indicate that PACT/RAX mediated regulation of PKR activity and eIF2α phosphorylation plays a role in cerebellar development and contributes to the dystonia phenotype resulting from this mutation.

Evaluation of the Stronger Together Peer Mentoring Model Among Patients With Breast and Gynecologic Cancer in Viet Nam

PURPOSE Stronger Together is a peer mentoring model that seeks to address the severe lack of mental health and psychosocial support for patients with cancer in many low- and middle-income countries (LMICs). This article presents the results of the Stronger Together pilot study among patients with breast and gynecologic cancer in Viet Nam (VN). METHODS Eligible participants comprised women age 25 years or older with a diagnosis of breast or gynecologic cancers and receiving treatment at four participating hospitals. Participants were asked whether they wanted to proceed with usual care or be matched with a trained and supervised peer mentor (a cancer survivor). Surveys were administered at baseline (0) and 2, 4, and 6 months and assessed depression, anxiety, stress, mental health and physical health components of quality of life (QOL), self-efficacy, and social support. We computed and compared 2-, 4-, and 6-month changes in scores from baseline and conducted difference-in-difference analyses to estimate the intervention effect at 6 months. RESULTS The sample size included N = 186 participants. Mentees (n = 91) exhibited improvements in depression, anxiety, stress, and mental health QOL across all time points, whereas usual care participants (n = 95) experienced these improvements at later periods (4 and 6 months). Compared with usual care participants, mentees reported greater improvements in depression at 2 and 4 months, mental health QOL at all time points, and self-efficacy and social support at 4 and 6 months. Greater improvements in stress were also seen in the breast cancer subsample. CONCLUSION Stronger Together is a promising model to improve mental health and psychosocial outcomes among patients with breast and gynecologic cancer in VN and can help fill gaps in cancer peer support interventions in many LMICs.

Examining the Effect of Resource Constraints on Teaching and Learning of Grade 12 Mathematics in Gauteng Community Learning Centres

The study focused on the effects of resource constraints on the teaching and learning of Grade 12 Mathematics in Gauteng Community Learning Centres (CLCs) in South Africa. It highlighted the historical and socio-economic context of apartheid and its enduring effects on educational inequalities. The lack of resources in CLCs, including substandard facilities, scarcity of teaching materials, and under-resourced teachers, was identified as a persistent issue. Grade 12 Mathematics is a vital subject for higher education and career paths, and proposed solutions include using deliverology and implementation science to mitigate these challenges.The methodology involved a multiple-case study design, with semi-structured interviews conducted with Grade 12 Mathematics teachers in CLCs in the Gauteng North region. Thematic analysis was used to analyze the qualitative data gathered from the interviews. The findings highlighted a severe lack of resources in CLCs, reliance on out-dated and borrowed materials, and a heavy burden on teachers to supply resources. Challenges included limited access to basic materials, financial and logistical strains on teachers, and a negative impact on teaching quality. Furthermore, the implications of these findings suggest that addressing resource constraints through these frameworks could significantly enhance the quality of Mathematics education in CLCs. The study recommends a strategic approach using deliverology and implementation science, focusing on structured goal setting, capacity building, stakeholder engagement, continuous improvement, policy advocacy, and technology integration to improve Grade 12 Mathematics delivery. These recommendations are aimed at mitigating the adverse effects of resource constraints and improving the teaching and learning of Grade 12 Mathematics in CLCs.

Topological conditions drive stability in meta-ecosystems

On a global level, ecological communities are being perturbed at an unprecedented rate by human activities and environmental instabilities. Yet, we understand little about what factors facilitate or impede long-term persistence of these communities. While observational studies indicate that increased biodiversity must, somehow, be driving stability, theoretical studies have argued the exact opposite viewpoint instead. This encouraged many researchers to participate in the ongoing debate. Within this context, however, there has been a severe lack of studies that consider spatial features explicitly, even though nearly all habitats are spatially embedded. To this end, we study here the linear stability of meta-ecosystems on networks that describe how discrete patches are connected by dispersal between them. By combining results from random-matrix theory and network theory, we are able to show that there are three distinct features that underlie stability: edge density, tendency to triadic closure, and isolation or fragmentation. Our results appear to further indicate that network sparsity does not necessarily reduce stability, and that connections between patches are just as important, if not more so, to consider when studying the stability of large ecological systems. Published by the American Physical Society 2024

Knowledge, practices,and barriers to access of emergency contraceptive pills in married women and men:a multicenter clinic-based cross-sectional study from Karachi, Pakistan.

Emergency contraceptive pills (ECPs) are significantly underutilized in many parts of the world, especially in South-Asia. Within Pakistan, despite the population surge, the utilization of ECPs remains alarmingly low. The purpose of this study was to investigate the knowledge and practices regarding ECPs amongst married women and men in Karachi, Pakistan and the possible barriers hindering access to and use of these contraceptives. A multi-centric cross-sectional study was conducted in Karachi, Pakistan. Interviews were conducted with participants using validated questionnaire involving different sections on demographics, knowledge, practices, and barriers to ECP use. Categorical variables were summarized as frequencies and percentages while continuous variables were characterized using mean and standard deviation. A chi-square test of variance was used for association between knowledge scores and different categorical values. A p-value of < 0.05 at 95% CI was statistically significant. Over half of the respondents (52.5%) were not using any method of contraception. 11.1% of respondents had used ECP at some point in their life. 337 (85.8%) participants had low knowledge, 55 (14%) had moderate while only 1 (0.25%) had high knowledge regarding ECPs. There was no significant association of knowledge scores with gender, age, employment status or parity. However, participants who had received counseling for family planning in the past or had previously used ECPs had significantly higher knowledge regarding ECPs. A majority 58% (221) of the participants expressed concerns about the potential side effects and 128 (33.9%) of them believed that ECPs were in contradiction to their religious and moral values. Our study in Karachi, Pakistan, highlights critical challenges in ECP awareness, utilization, and family planning. Although the results show improved ECP usage than studies previously done in Pakistan, there is a further need to increase the reach of ECPs through a variety of methods. Persistent myths and misconceptions and a severe lack of awareness further hinders their use.

Pharmacogenetic testing to optimize psychopharmacotherapy: Case study of a patient with severe depression and lack of treatment success due to genetic polymorphisms for CYP2D6 and CYP2C19

Pharmacogenetic testing to optimize psychopharmacotherapy: Case study of a patient with severe depression and lack of treatment success due to genetic polymorphisms for CYP2D6 and CYP2C19

Reconstructing Tibetan Plateau lake bathymetry using ICESat-2 photon-counting laser altimetry

Lake bathymetry is important for quantifying and characterizing underwater morphology and its geophysical state, which is critical for hydrological and ecological studies. Due primarily to the harsh environment of the Tibetan Plateau, there is a severe lack of lake bathymetry measurements, limiting the accurate estimation of total lake volumes and their evolutions. Here, we propose a novel lake bathymetry reconstruction by combining ICESat-2/ATLAS (Advanced Topography Laser Altimetry System) data with a numerical model. An improved grid-based photon noise removal method is used to address the photon signal buried in the background noise during the local daytime. The developed model was validated for seven lakes on the Tibetan Plateau and showed good agreement between simulated and measured lake volumes, with an average absolute percentage error of 8.0 % for maximum water depth and 19.7 % for lake volume simulations. The model was then utilized to estimate the water volume of other lakes by combining it with the self-affine theory. The lake depths obtained from ICESat-2/ATLAS show good agreement (RMSE = 0.69 m; rRMSE = 10.3 %) with available in-situ measurements for lakes with depths <16.5 m, demonstrating the potential of ICESat-2/ATLAS for improved reconstruction of the bathymetry of clear water inland lakes. Our study reveals for the first time, that the Tibetan Plateau has an estimated total lake water volume of 1043.69 ± 341.31 km3 for 33,477 lakes (>0.01 km2) in 2022. Over 70 % (∼734.8 km3) of the lake water storage is concentrated in the Inner Plateau, with the Yellow River basin accounting for 10.9 % (∼113.9 km3), followed by the Indus River basin with 7.2 % (∼75.1 km3). Our study provides a robust method for estimating total lake volumes where in-situ measurements are scarce and can be extended to other clear water lakes, thus contributing to more accurate global assessments and towards comprehensive quantification of Earth's surface water resources distribution.

Research on the effect of training program based on service-oriented leadership theory on nurses' job burnout

Objective: To explore the effect of training program based on service-oriented leadership theory on alleviating the degree of job burnout of clinical nurses, and provide reference for improving the situation of job burnout of nurses. Methods: From January to December 2023, 10 head nurses of a Grade A general hospital were selected by random number table method for training, and 5 nurses were selected from the department of each head nurse by random number table method, a total of 50 nurses were selected as research objects. Through the training program based on the service-oriented leadership theory, the selected head nurses were trained on the service-oriented leadership theory, job burnout and burnout mitigation methods and passed the examination. The training period was 2 months. The general data of 50 nurses were collected, and the job burnout of nurses was investigated by using the Maslach Burnout Inventory before and 6 months after the training of head nurses, and the changes of scores of each dimension were compared by paired t-test. Results: The nurses were (30.4±5.5) years old and their working life was (8.1±6.1) years. The total detection rate of job burnout before training was 100% (50/50), the detection rate of moderate to severe emotional exhaustion was 60% (30/50), and the detection rate after training was 36% (18/50). The detection rate of moderate to severe depersonalization was 72% (36/50) and 40% (20/50) after training. The detection rate of moderate to severe lack of job accomplishment was 86% (43/50) and 54% (27/50) after training. After 6 months of head nurses training, the scores of emotional exhaustion and depersonalization of nurses were significantly lower than those before training, while the scores of personal achievement were significantly higher than those before training, with statistical significances (P<0.05) . Conclusion: The training program based on service-oriented leadership theory can scientifically prevent and alleviate nurses' job burnout after receiving training of administrators, which is helpful to improve the current situation of nurses' job burnout and reduce the degree of nurses' job burnout, and can play a positive role in promoting nurses' physical and mental health.

Replantation After Dental Avulsion: A Scoping Review and Proposal of a Flow Chart.

Dental avulsion, the complete displacement of a tooth from its socket, is a severe dental trauma with a prevalence of 0.5% to 16% of all dental injuries. Replantation of avulsed teeth is common, yet recent studies show high failure rates and unpredictable long-term outcomes. This review examines clinical variables influencing intentional dental replantation decisions and proposes a treatment flow chart. A comprehensive literature search was conducted in PubMed-Medline, Scopus, WoS, and Cochrane databases using the keywords "tooth avulsion," "tooth replantation," and "tooth ankylosis." Inclusion criteria encompassed studies from January 2018 to February 2024. From 752 identified articles, 9 systematic reviews including 3 meta-analyses were selected for this scoping review. Immediate replantation is the gold standard for avulsed teeth, yet delayed replantation is more common in practice, impacting survival rates. Adherence to guidelines from the International Association on Dental Traumatology improves outcomes, especially in paediatric patients. Factors such as multiple caries, severe periodontal disease, advanced age, psychological conditions, immunodeficiency, and lack of cooperation are contraindications for replantation. Despite the high failure rate, replantation remains recommended in literature due to its potential advantages over prosthetic implants. This review highlights the complexities in decision-making for dental replantation, emphasising the need for a comprehensive approach considering individual clinical cases. A proposed treatment flow chart aims to support clinicians in predicting prognosis and making informed decisions. The review also underscores the link between dental trauma, poor oral health, and potential neglect in children, highlighting the importance of preventive measures and parental awareness.

Deep Interactive Segmentation of Medical Images: A Systematic Review and Taxonomy.

Interactive segmentation is a crucial research area in medical image analysis aiming to boost the efficiency of costly annotations by incorporating human feedback. This feedback takes the form of clicks, scribbles, or masks and allows for iterative refinement of the model output so as to efficiently guide the system towards the desired behavior. In recent years, deep learning-based approaches have propelled results to a new level causing a rapid growth in the field with 121 methods proposed in the medical imaging domain alone. In this review, we provide a structured overview of this emerging field featuring a comprehensive taxonomy, a systematic review of existing methods, and an in-depth analysis of current practices. Based on these contributions, we discuss the challenges and opportunities in the field. For instance, we find that there is a severe lack of comparison across methods which needs to be tackled by standardized baselines and benchmarks.

A Proposal of Behavior-Based Consumption Profiles for Green Software Design

Despite the increase in the efficiency of energy consumption in information and communication technology, software execution and its constraints are responsible for how energy is consumed in hardware hosts. Consequently, researchers have promoted the development of sustainable software with new development methods and tools to lessen its hardware demands. However, the approaches developed so far lack cohesiveness along the stages of the software development life cycle (SDLC) and exist outside of a holistic method for green software development (GSD). In addition, there is a severe lack of approaches that target the analysis and design stages of the SDLC, leaving software architects and designers unsupported. In this article, we introduce our behavior-based consumption profile (BBCP) external Domain-Specific Language (DSL), aimed at assisting software architects and designers in modeling the behavior of software. The models generated with our external DSL contain multiple sets of properties that characterize features of the software’s behavior. In contrast to other modeling languages, our BBCP emphasizes how time and probability are involved in software execution and its evolution over time, helping its users to gather an expectation of software usage and hardware consumption from the initial stages of software development. To illustrate the feasibility and benefits of our proposal, we conclude with an analysis of the model of a software service created using the BBCP, which is simulated using Insight Maker to obtain an estimation of hardware consumption and later translated to energy consumption.

The gendered dimensions of small-scale fishing activities: A case study from coastal Kenya

Although women contribute substantially to the small-scale fisheries sector globally, in many countries there is a severe lack of gender-disaggregated data on fishing activities. This gender data gap hampers a comprehensive understanding of small-scale fisheries dynamics with implications for fisheries management and food security. In this study, we investigate women's and men's engagement in small-scale fishing through a case study in coastal Kenya, a region characterized by a high dependence on fisheries for local livelihoods and nutritional needs. We applied a mixed method approach, combining participant observation, photography, semi-structured interviews on gender identities (n = 11) and gendered fishing practices (n = 28), an individual survey (n = 141), and pebble games (n = 35). Our results reveal a marked gendered division of labor across the seascape, with women mostly fishing in intertidal areas and men beyond the reef. Further, we find that women's fishing practices are characterized by less fishing gear, less catch, a lower functional diversity of catches, less fishing effort, and less income than those of men. However, women's catches contribute significantly to local diets, accounting for up to 50% of the fish and seafood consumed in fisherwomen-headed households. Despite women's fishing activities appearing less productive and profitable that those of men, they are important for achieving food security in Kenyan coastal communities. Results from this study contribute to broadening our understanding of the gendered dimensions of small-scale fishing and highlight relevant information for developing gender-inclusive management strategies. We conclude by providing key recommendations for fisheries research, management, and governance.

Improve operational flexibility of distribution systems using transportable resources

With the continuous progress of carbon neutrality, the accelerating integration of distributed renewable energy sources (RES) poses tremendous pressure on distribution systems' safe and stable operation. The distribution systems that cannot be upgraded in time, e.g., those in border areas, are hard to adapt to the large-scale integration of RES and the growing energy demand, facing a severe lack of operational flexibility. In light of this, the integrated mobile energy station (IMES), which consists of a battery system and photovoltaic cells, is used to improve operational flexibility and alleviate the need for upgrades. An adaptive robust allocation and dispatch model is introduced to coordinate the operation of the distribution system and IMES under multiple uncertainties. The first stage of the proposed model optimizes the locations of IMES using the forecast information of RES and loads, while the second stage optimizes the dispatch plan that is adaptive to the realization of uncertainties. Since the uncertain photovoltaic power in the IMES depends on its deployment location, the proposed model is an adaptive robust optimization with decision-dependent uncertainty, bringing great challenges to the solution. To solve it efficiently, a warmstart-enhanced column-and-constraint generation algorithm is introduced, in which the bi-level subproblem is solved by the dual method and outer approximation algorithm. Finally, case studies demonstrate the effectiveness of the proposed method. The participation of six IMESs can save 5.23 % on the system's total cost and avoid the load shedding caused by transmission congestion, indicating IMES's potential for economical and flexible operation of the system.

GaSI: A Wide-Gap Non-centrosymmetric Helical Crystal.

The complex non-centrosymmetric and chiral nature of helical structures endow materials that possess such motifs with unusual properties. However, despite their ubiquity in biological and organic systems, there is a severe lack of inorganic crystals that display helicity in extended lattices, where these unusual properties are expected to be most pronounced. Here, we report a new inorganic helical structure, gallium sulfur iodide (GaSI), within the exfoliable class of III-VI-VII (1:1:1) one-dimensional (1D) van der Waals (vdW) crystals. Through detailed structural analyses, including single-crystal X-ray diffraction, electron microscopy, and density functional theory (DFT), we elucidate the apparent noncrystallographic screw axis and the first example of an atomic scale helical structure bearing a "squircular" cross-section in GaSI. Crystallizing in the non-centrosymmetric P4̅ space group, we found that GaSI crystals exhibit pronounced second-harmonic generation. From diffuse reflectance spectroscopy, GaSI displays a sizeable bandgap of 3.69 eV, owing tostrong covalent interactions arising from the smaller sulfur atoms within the helix core. These results position GaSI as a promising exfoliable nonlinear optical material across a broad optical window.

Towards AI-Assisted Synthesis of Verified Dafny Methods

Large language models show great promise in many domains, including programming. A promise is easy to make but hard to keep, and language models often fail to keep their promises, generating erroneous code. A promising avenue to keep models honest is to incorporate formal verification: generating programs’ specifications as well as code so that the code can be proved correct with respect to the specifications. Unfortunately, existing large language models show a severe lack of proficiency in verified programming. In this paper, we demonstrate how to improve two pretrained models’ proficiency in the Dafny verification-aware language. Using 178 problems from the MBPP dataset, we prompt two contemporary models (GPT-4 and PaLM-2) to synthesize Dafny methods. We use three different types of prompts: a direct Contextless prompt; a Signature prompt that includes a method signature and test cases, and a Chain of Thought (CoT) prompt that decomposes the problem into steps and includes retrieval augmentation generated example problems and solutions. Our results show that GPT-4 performs better than PaLM-2 on these tasks and that both models perform best with the retrieval augmentation generated CoT prompt. GPT-4 was able to generate verified, human-evaluated, Dafny methods for 58% of the problems, however, GPT-4 managed only 19% of the problems with the Contextless prompt, and even fewer (10%) for the Signature prompt. We are thus able to contribute 153 verified Dafny solutions to MBPP problems, 50 that we wrote manually, and 103 synthesized by GPT-4. Our results demonstrate that the benefits of formal program verification are now within reach of code generating large language models. Likewise, program verification systems can benefit from large language models, whether to synthesize code wholesale, to generate specifications, or to act as a "programmer’s verification apprentice", to construct annotations such as loop invariants which are hard for programmers to write or verification tools to find. Finally, we expect that the approach we have pioneered here — generating candidate solutions that are subsequently formally checked for correctness — should transfer to other domains (e.g., legal arguments, transport signaling, structural engineering) where solutions must be correct, where that correctness must be demonstrated, explained and understood by designers and end-users.

ELFN1 is a new extracellular matrix (ECM)-associated protein

AimsThe ELFN1, discovered in 2007, is a single-pass transmembrane protein. Studies conducted thus far to elucidate the function of the Elfn1 have been limited only to animal studies. These studies have reported that ELFN1 is a universal binding partner of metabotropic glutamate receptors (mGluRs) in the central nervous system and its functional deficiency has been associated with the pathogenesis of neurological and neuropsychiatric diseases. In 2021, we described the first disease-associated human ELFN1 pathogenic gene mutation. Severe joint laxity, which was the most striking finding of this new disease and was clearly seen in the patients since early infancy, showed that the ELFN1 may have a possible function in the connective tissue besides the nervous system. Here, we present the first experimental evidence of the extracellular matrix (ECM)-related function of the ELFN1. Materials and methodsPrimary skin fibroblasts were isolated from the skin biopsies of ELFN1 mutated patients and healthy foreskin donors. For the clinical trial in a dish, in vitro ECM and DEM (decellularized ECM) models were created from skin fibroblasts. All the in vitro models were comparatively characterized and analyzed. Key findingsThe mutation in the ELFN1 signal peptide region of patients resulted in a severe lack of ELFN1 expression and dramatically altered the characteristic morphology and behavior (growth, proliferation, and motility) of fibroblasts. SignificanceWe propose that ELFN1 is involved in the cell-ECM attachment, and its deficiency is critical enough to cause a loss of cell motility and soft ECM stiffness.

Standardization Gaps in European Disaster Management

Abstract The management of large-scale disasters, caused for example by natural hazards, industrial accidents or terror attacks, requires collaboration of different types of organizations. The organizations can use different equipment and tools, follow different strategies and procedures, or have different understandings of relevant terms. These differences, increasingly complex when it comes to international cooperation, can cause severe lack of interoperability that can result in vital time delays. An approach to increase interoperability in European disaster management is to standardize solutions, such as technical tools, procedures or terminology. However, standardization is not always trivial, in some cases it is impossible, in others there are challenges to overcome. In context of an EU initiative to facilitate and push standardization across all fields of European disaster management, an initial step was to gather standardization gaps in a comprehensive manner. Standardization gaps are the result of comparing end-users’ standardization needs with existing standards. Selected results of the gap analysis are presented in this article, and put into context of the general structure of disaster management standardization. Related challenges such as the proper involvement of all relevant stakeholders, and specific characteristics of the disaster management domain are addressed, and suggestions for a way forward are provided.

Academic Integrity in Existing Classroom Resources and Teaching Learning Process for Children with Vision Impairment in Government Special Education Institutions of Punjab Pakistan

Purpose: The objective of this qualitative study was to evaluate the level of academic integrity in the provision and utilization of classroom resources and flow of the teaching-learning process for children with vision impairment (CWVI) at primary level. Design/Methodology/Approach: Non-participant classroom observations were conducted. Eight special education institutions working in various districts of Punjab were randomly selected. A self-developed, field experts validated classroom observation checklist was applied to conduct the classroom observations. All observations were carried out personally by the principal author. Researchers analyzed the data by descriptive statistics percentages of observed indicators for academic integrity. After that, a thematic analysis was carried out. Findings: The study showed that most observed classes had satisfactory classroom arrangement, teacher competence and classroom illumination. However, many observed classrooms were found with inadequate classroom arrangements and disturbing physical environment. There is a severe lack about effective use of need-based equipment, assistive aids, low-vision devices, lesson plans, student portfolios and any record of Students’ previous performance. Implications/Originality/Value: The study suggested that special education institutions should make all lacking facilities available. Refresher courses should be provided to teachers to improve their personality and teaching skills. The presence of Students’ portfolios and lesson plans should be assured.

BearingFM: Towards a foundation model for bearing fault diagnosis by domain knowledge and contrastive learning

Monitoring bearing failures in production equipment can effectively prevent finished product quality issues and unplanned factory downtime, thereby reducing supply chain uncertainties and risk. Therefore, monitoring bearing failures in production equipment is important for improving supply chain sustainability. Due to the generalization limitations of neural network models, specific models must be trained for specific tasks. However, in real industrial scenarios, there is a severe lack of labeled samples, making it difficult to deploy fault diagnosis models across massive amounts of equipment in workshops. In order to solve the above issue, this paper proposes a cloud-edge-end collaborative semi-supervised learning framework, which provides multi-level computing power and data support for building a foundation model. A data augmentation method based on the bearing fault mechanism is proposed, which effectively preserves the inherent essential characteristics in vibration signals by normalizing frequency and adding noise in specific frequency bands. A novel contrastive learning model is designed, which narrows the distances between positive samples and widens the distances between negative samples in the high-dimensional space through cross comparisons in the time dimension and knowledge dimension, thereby extracting the most essential characteristics from the unlabeled signals. Multiple sets of experiments conducted on four datasets demonstrate that the proposed approach achieves an approximately 98% fault classification accuracy with only 1.2% labeled samples.