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Ultrasound has proven to have great potentials in the diagnosis and work-up of patients affected by tropical diseases. Its role in the diagnosis of malaria and typhoid abounds, but its value as a triaging tool in a resource-constrained settings is indistinct. Our review aimed is aimed at assessing the utility of ultrasound in diagnosis and prognosis of malaria and typhoid. Extensive literature search was conducted using the PubMed electronic database, for original peer reviewed articles in English language within 1964–2023. Keywords like "malaria", "typhoid", "S. Typhi", "Salmonella Typhi", "enteric fever", "ultrasound", "sonography" and "ultrasonography" were searched, using Boolean operators such as (OR, AND) applying the following filters (English, Human). A systematic synthesis of the literature was done. Our initial search yielded 749 potentially relevant references out of which 55 were found to be eligible. Organs assessed include the liver, spleen, kidneys, intestines, mesenteric lymph nodes, among others. For malaria, pathognomonic conditions like splenic enlargement, hepatomegaly, renal abnormalities as well as mesenteric lymph nodes and intestinal wall thickening in patients with typhoid fever. Ultrasound by experienced clinicians adds significantly to the diagnosis and work-up of patients with malaria and typhoid fever. However, it is important to note that ultrasound alone may not be sufficient for definitive diagnosis as laboratory tests may still be required for confirmatory diagnosis. This study provide information on ultrasound in diagnosis of Malaria and typhoid by evaluating the morphological changes in abdominal and other organs of the body. This can be a guide to clinicians and other healthcare providers for early diagnosis and work-up of patients in endemic areas where resources are scarce. [ABSTRACT FROM AUTHOR]

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Federated learning (FL) is a decentralized and privacy-preserving machine learning technique that protects data privacy by learning models locally and not sharing datasets. However, due to limited computing resources on devices and highly heterogeneous data in practical situations, the training efficiency and resource utilization of federated learning is low. In order to resolve these challenges, we introduce a blockchain-assisted dynamic adaptive and personalized federated learning framework (TV-FedAvg) in the presence of restricted computing power resources and data heterogeneity. After each round of local training, we utilize an improved scoring model based on VIKOR and TOPSIS to comprehensively score the devices. The scores are then utilized to choose devices for participation in global aggregation and to carry out model aggregation through blockchain consensus. Furthermore, resources are reallocated for the next round to enhance resource efficiency, model fairness, and performance. Finally, we demonstrate through experimentation that TV-FedAvg outperforms other models such as pFedMe, FedAvg, Per-FedAvg, and TOPSIS in terms of both efficiency and performance. [ABSTRACT FROM AUTHOR]

Cloud computing and the increasing popularity of 5G have greatly increased the application of images on Internet of Things (IoT) devices. The storage of images on an untrusted cloud has high security and privacy risks. Several lightweight cryptosystems have been proposed in the literature as appropriate for resource-constrained IoT devices. These existing lightweight cryptosystems are, however, not only at the risk of compromising the integrity and security of the data but also, due to the use of substitution boxes (S-boxes), require more memory space for their implementation. In this paper, a secure lightweight cryptography algorithm, that eliminates the use of an S-box, has been proposed. An algorithm termed Enc, that accepts a block of size n divides the block into L n R bits of equal length and outputs the encrypted block as follows: E = L ⨂ R ⨁ R , where ⨂ and ⨁ are exclusive-or and concatenation operators, respectively, was created. A hash result, h a s R = S H A 256 P ⨁ K , was obtained, where SHA256, P, and K are the Secure Hash Algorithm (SHA−256), the encryption key, and plain image, respectively. A seed, S, generated from e n c h a s h = E n c h a s h e n c , K , where hashenc is the first n bits of hasR, was used to generate a random image, Rim. An intermediate image, i n t i m a g e = R i m ⨂ P , and cipher image, C = E n c i n t i m a g e , K , were obtained. The proposed scheme was evaluated for encryption quality, decryption quality, system sensitivity, and statistical analyses using various security metrics. The results of the evaluation showed that the proposed scheme has excellent encryption and decryption qualities that are very sensitive to changes in both key and plain images, and resistance to various statistical attacks alongside other security attacks. Based on the result of the security evaluation of the proposed cryptosystem termed Hash XOR Permutation (HXP), the study concluded that the security of the cryptography algorithm can still be maintained without the use of a substitution box. [ABSTRACT FROM AUTHOR]

The Multi-skilled Resource Constrained Project Scheduling Problem (MS-RCPSP) is a complex and multi-faceted problem that involves scheduling activities whilst considering various resource constraints. These constraints include limited availability of workers, equipment, and materials, with each activity requiring a minimal set of skills to be executed. Furthermore, for a better resemblance to reality, workers/machines are assumed to be multi-skilled/multi-purpose posing another dimension of complexity to the problem. The objective is to minimize project duration, cost, or other relevant criteria while accounting for the inherent resources flexibility. This paper provides a systematic review of the literature pertaining to MS-RCPSP, and an in-depth analysis of 171 papers published between 2000 and 2021 inclusive. The conducted bibliometric analysis identifies the top contributing authors, most influential papers, existing research tendencies, and thematic research topics within the field. In addition, this review highlights different aspects of the MS-RCPSP, spanning the significance of performance measures, solution approaches, application areas, and the incorporation of time constraints. While project completion time, cost, and tardiness are common performance indicators, other measures such as multi-skilled staff assignment and schedule robustness are also deemed important. Although various methods have been employed to solve the MS-RCPSP including exact and approximate approaches, the selection of the most-suited approach depends on the problem’s scale, complexity, and constraints, necessitating careful consideration of each method’s strengths and weaknesses. Interestingly, several studies have jointly addressed resource and time constraints in the context of MS-RCPSP, often considering tardiness, and have proposed different algorithms, models, and metaheuristics to tackle these challenges. This paper clearly highlights research gaps and promising avenues for future research. This work provides valuable insights for project managers to effectively schedule tasks in the presence of multiple flexible resources.

The Internet of Things (IoT) has emerged as a revolutionary communication technology, enabling the connection of resource-limited devices to the Internet. These devices are deployed in various industrial control systems to remotely monitor and control industrial applications. However, the public Internet’s inherent vulnerability to malicious attacks poses a significant challenge to the secure operation of these systems. To address this challenge, a lightweight and efficient authentication framework, LEAF-IIoT, is proposed. LEAF-IIoT leverages authenticated encryption (AE) techniques to provide a multifaceted security solution encompassing confidentiality, authentication, and data integrity. It establishes a secure channel by exchanging messages between the user, gateway, and smart embedded device, culminating in the creation of a session key for secure data exchange. Rigorous security assessment confirms the robustness of LEAF-IIoT, while performance evaluation demonstrates its significantly lower computational cost and reduced communication overhead compared to existing frameworks. Despite these efficiencies, LEAF-IIoT continues to provide strong security features, ensuring the integrity and confidentiality of data exchanged in the IIoT context.

Smart manufacturing systems combine sensor systems and manufacturing processes, and they have been widely adopted in the industry to solve real production problems, help manufacturing enterprises achieve rapid decision-making, and improve manufacturing value. However, manufacturing enterprises still face huge challenges with the coexistence of continuously changing dynamic demands, collaborative scheduling of dynamic resources, precise matching of manufacturing resources, and multiple resource constraints. To address this challenge, this research combines digital twin (DT) technology to propose a smart site-selection system with dynamic resource-accurate matching characteristics based on the attributes and associations of both resource sides, supply and demand sides, and site-selection sides, which can integrate and optimize resources according to the requirements of manufacturing tasks. In addition, by establishing the discovery mechanism of bottleneck processes and resource allocation methods, generating configuration priorities, and thus reducing the solution space for resource allocation, the precise allocation of limited resources is achieved more quickly and easily, and the scheduling chaos in the parallel scheduling of multiple resources is solved and the multi-objective robust optimization model is solved by combining smart optimization algorithms. Combined with the example analysis, the results show that the smart site-selection system and multi-resource cyclic allocation mechanism proposed in this paper can collaboratively match a large amount of dynamic resources, and the utilization rate of idle manufacturing resources can be increased by 60%. This research effectively realizes the optimal allocation of multiple manufacturing resources in a resource-constrained environment and helps manufacturing enterprises create more manufacturing value. [ABSTRACT FROM AUTHOR]

This paper introduces a comprehensive framework that elucidates the microfoundations of data-driven antimicrobial stewardship programs (ASPs), specifically focusing on resource-constrained settings. Such settings necessitate the utilization of available resources and engagement among multiple stakeholders. The microfoundations are conceptualized as interlinked components: input, process, output, and outcome. Collectively, these components provide a comprehensive framework for understanding the development and implementation of data-driven ASPs in resource-constrained settings. It underscores the importance of considering both the social and material dimensions when evaluating microbiological, clinical, and social impacts. By harmonizing technology, practices, values, and behaviors, this framework offers valuable insights for the development, implementation, and assessment of ASPs tailored to resource-constrained environments. [ABSTRACT FROM AUTHOR]

This paper investigates three substitution box (S-box) designs for lightweight ciphers. The proposed designs involve functional decomposition, which is preferable as compared to the look-up tables or logic gates-based S-box designs due to their advantages, as outlined in this paper. The aim is to reduce the number of literals at the input of the S-box to achieve resource reduction in the overall circuit design of the encryption algorithms. The proposed S-box architectures provide optimized resource mapping for specific target hardware, and high throughput along with lesser energy consumption compared to state-of-the-art designs. The proposed S-box designs are applied to the substitution layers of symmetric lightweight block ciphers with a standard security level. In order to be fair in comparison, the overall cipher designs are targeted for similar FPGA-based implementation as used in existing works, while the architectures of the individual 4-bit S-boxes are evaluated using SAED90 nm standard cell libraries. The performance of the proposed S-box designs is observed to be superior at RFID and ISM frequency ranges which can be deployed in applications constrained to low resources as well as demanding high performance and medium security. • Three S-box architectures are proposed using functional decomposition techniques. • The proposed designs are applied to the substitution layer of each cipher i.e., GIFT, Midori, PRESENT and RECTANGLE. • The throughput and energy of the architectures are evaluated for RFID and ISM band frequencies to manifest the utility of lightweight ciphers in IoT applications. [ABSTRACT FROM AUTHOR]

Abstract Issue: Health professions education (HPE) is intimately linked with teaching and learning in the clinical environment. While the value of authentic clinical experiences is acknowledged, whether learning actually occurs is to a large extent dependent on students’ behaviors and attitudes. The kinds of student behaviors and attitudes that are necessary to optimize learning in the clinical environment thus becomes relevant. Evidence: Tips and recommendations to maximize clinical learning in a variety of settings have been well documented. There is, however, a dearth of literature which takes a narrative-based praxis approach focused on resource-constrained environments. We developed this praxis-orientated article as a means to translate the available literature and theory into a simple, practical guide, focused on optimizing clinical learning from a student perspective, remaining cognizant of the particular challenges present in a resource-constrained setting. Implications: Based on the resource-constrained environments our students are exposed to, we outline the following six key aspects: student-driven learning, integration into the community of practice, student engagement, empathy, interprofessional learning opportunities, and feedback for learning. These aspects provide useful pointers for students in general. Furthermore, exploration into what strategies students may utilize in resource-constrained clinical contexts is addressed. [ABSTRACT FROM AUTHOR]

Cloud computing and the increasing popularity of 5G have greatly increased the application of images on Internet of Things (IoT) devices. The storage of images on an untrusted cloud has high security and privacy risks. Several lightweight cryptosystems have been proposed in the literature as appropriate for resource-constrained IoT devices. These existing lightweight cryptosystems are, however, not only at the risk of compromising the integrity and security of the data but also, due to the use of substitution boxes (S-boxes), require more memory space for their implementation. In this paper, a secure lightweight cryptography algorithm, that eliminates the use of an S-box, has been proposed. An algorithm termed Enc, that accepts a block of size n divides the block into L n R bits of equal length and outputs the encrypted block as follows: E=L⨂R⨁R, where ⨂ and ⨁ are exclusive-or and concatenation operators, respectively, was created. A hash result, hasR=SHA256P⨁K, was obtained, where SHA256, P, and K are the Secure Hash Algorithm (SHA−256), the encryption key, and plain image, respectively. A seed, S, generated from enchash=Enchashenc,K, where hashenc is the first n bits of hasR, was used to generate a random image, Rim. An intermediate image, intimage=Rim⨂P, and cipher image, C=Encintimage,K, were obtained. The proposed scheme was evaluated for encryption quality, decryption quality, system sensitivity, and statistical analyses using various security metrics. The results of the evaluation showed that the proposed scheme has excellent encryption and decryption qualities that are very sensitive to changes in both key and plain images, and resistance to various statistical attacks alongside other security attacks. Based on the result of the security evaluation of the proposed cryptosystem termed Hash XOR Permutation (HXP), the study concluded that the security of the cryptography algorithm can still be maintained without the use of a substitution box.

Antimicrobial Resistance (AMR) is one of society’s most urgent global issues, requiring urgent multidisciplinary-based research and practice approaches to engage with these policies. Several global and national policy statements have been released in the last two decades, particularly emphasising the strengthening of the digital surveillance system. However, implementing these initiatives remains patchy, particularly in the context of public health systems in Low- and Middle-Income Countries. This paper argues that one of the significant reasons contributing to this sub-optimal uptake of these systems is that the top-down implementation models do not adequately cater to the needs, aspirations, and capacities of the health facility staff, who, ultimately, are the end users of the system. The paper highlights the importance of digital technology in healthcare facilities with resource constraints to promote the responsible use of antibiotics. It discusses the process of developing an evidence base for action in low- and middle-income countries (LMICs) through digitally mediated data-driven policy. This process is conceptualised as a three-phase process, which involves stabilising data entry, generating outcomes, and taking action at the local level. The paper argues the need for bottom-up implementation models, which emphasise the need to understand the practices users engage with in their everyday work and design the digital system to add value and not work to these everyday practices. The paper emphasises the importance of building local capacities to develop effective and sustainable antimicrobial stewardship (AMS) programs through enabling networking around digital solutions, creating value in networked partnerships, initiating conversations around data, and raising awareness of the digital to develop AMS programs.

Abstract Anant Ramaswamy Introduction The overall survival (OS) of metastatic colorectal cancers (mCRCs) in clinical practice and resource-constrained low- and middle-income countries (LMICS) like India is not known. Materials and Methods Data of patients with mCRC treated between January 2013 and August 2017 were accessed from a prospectively maintained database. Demographics, disease characteristics, chemotherapeutic regimens, use of monoclonal antibodies, and survival outcomes in treated patients were collected and analyzed. Costs of treatment options as off 2017 were also interpreted. Results The data of 403 patients satisfied prespecified inclusion criteria and were included for analysis. The median age of the cohort was 48 years (range: 17–86) with a predominance of rectal cancers (63.3%), liver alone metastases (47.1%), and resected primary (69.7%). Signet ring histology was present in 82 patients (20.3%). The most commonly used first-line regimen (CT1) was modified capecitabine-oxaliplatin (53.3%). Two hundred and nineteen patients (54.3%) received second-line systemic therapy (CT2). Patients received a median of two lines of therapy (range: 1–6). MoAbs were used by 48 patients (13.4%) with CT1 and 34 patients (15.5%) with CT2. Median OS of the entire cohort was 17.61 months (95% confidence interval: 15.48–19.74), which was within the predicted range, as per investigator hypothesis. The presence of signet ring histology (p

This paper introduces a comprehensive framework that elucidates the microfoundations of data-driven antimicrobial stewardship programs (ASPs), specifically focusing on resource-constrained settings. Such settings necessitate the utilization of available resources and engagement among multiple stakeholders. The microfoundations are conceptualized as interlinked components: input, process, output, and outcome. Collectively, these components provide a comprehensive framework for understanding the development and implementation of data-driven ASPs in resource-constrained settings. It underscores the importance of considering both the social and material dimensions when evaluating microbiological, clinical, and social impacts. By harmonizing technology, practices, values, and behaviors, this framework offers valuable insights for the development, implementation, and assessment of ASPs tailored to resource-constrained environments.

Purpose: To develop a set of actionable quality indicators for critical care suitable for use in low- or middle-income countries (LMICs).Methods: A list of 84 candidate indicators compiled from a previous literature review and stakeholder recommendations were categorised into three domains (foundation, process, and quality impact). An expert panel (EP) representing stakeholders from critical care and allied specialties in multiple low-, middle-, and high-income countries was convened. In rounds one and two of the Delphi exercise, the EP appraised (Likert scale 1-5) each indicator for validity, feasibility; in round three sensitivity to change, and reliability were additionally appraised. Potential barriers and facilitators to implementation of the quality indicators were also reported in this round. Median score and interquartile range (IQR) were used to determine consensus; indicators with consensus disagreement (median < 4, IQR ≤ 1) were removed, and indicators with consensus agreement (median ≥ 4, IQR ≤ 1) or no consensus were retained. In round four, indicators were prioritised based on their ability to impact cost of care to the provider and recipient, staff well-being, patient safety, and patient-centred outcomes.Results: Seventy-one experts from 30 countries (n = 45, 63%, representing critical care) selected 57 indicators to assess quality of care in intensive care unit (ICU) in LMICs: 16 foundation, 27 process, and 14 quality impact indicators after round three. Round 4 resulted in 14 prioritised indicators. Fifty-seven respondents reported barriers and facilitators, of which electronic registry-embedded data collection was the biggest perceived facilitator to implementation (n = 54/57, 95%) Concerns over burden of data collection (n = 53/57, 93%) and variations in definition (n = 45/57, 79%) were perceived as the greatest barrier to implementation.Conclusion: This consensus exercise provides a common set of indicators to support benchmarking and quality improvement programs for critical care populations in LMICs. [ABSTRACT FROM AUTHOR]

Background: There is limited access to 1 year of adjuvant trastuzumab in resource-constrained settings. Most randomized studies have failed to prove non-inferiority of shorter durations of adjuvant trastuzumab compared to 1 year However, shorter durations are often used when 1 year is not financially viable. We report the outcomes with 12 weeks of trastuzumab administered as part of curative-intent treatment.Methods: This is a retrospective analysis of patients treated at Tata Memorial Centre, Mumbai, a tertiary care cancer center in India. Patients with human epidermal growth factor receptor (HER2)-positive early or locally advanced breast cancer who received 12 weeks of adjuvant or neoadjuvant trastuzumab with paclitaxel and four cycles of an anthracycline-based regimen in either sequence, through a patient assistance program between January 2011 and December 2012, were analyzed for disease-free survival (DFS), overall survival (OS), and toxicity.Results: A total of 102 patients were analyzed with a data cutoff in September 2019. The median follow-up was 72 months (range 6-90 months), the median age was 46 (24-65) years, 51 (50%) were postmenopausal, 37 (36%) were hormone receptor-positive, and 61 (60%) had stage-III disease. There were 37 DFS events and 26 had OS events. The 5-year DFS was 66% (95% Confidence Interval [CI] 56-75%) and the OS was 76% (95% CI 67-85%), respectively. Cardiac dysfunction developed in 11 (10.7%) patients.Conclusion: The use of neoadjuvant or adjuvant 12-week trastuzumab-paclitaxel in sequence with four anthracycline-based regimens resulted in acceptable long-term outcomes in a group of patients, most of whom had advanced-stage nonmetastatic breast cancer. [ABSTRACT FROM AUTHOR]

There is an increasing demand for Internet of Things (IoT) networks consisting of resource-constrained devices executing increasingly complex applications. Due to these resource constraints, IoT devices will not be able to execute expensive tasks. One solution is to offload expensive tasks to resource-rich edge nodes, which requires a framework that facilitates the selection of suitable edge nodes to perform task offloading. Therefore, in this article, we present a novel trust-model-driven system architecture, based on behavioral evidence, that is suitable for resource-constrained IoT devices and supports computation offloading. We demonstrate the viability of the proposed architecture with an example deployment of the Beta Reputation System trust model on real hardware to capture node behaviors. The open environment of edge-based IoT networks means that threats against edge nodes can lead to deviation from expected behavior. Hence, we perform a threat modeling to identify such threats. The proposed system architecture includes threat handling mechanisms that provide security properties such as confidentiality, authentication, and non-repudiation of messages in required scenarios and operate within the resource constraints. We evaluate the efficacy of the threat handling mechanisms and identify future work for the standards used. [ABSTRACT FROM AUTHOR]

Effective disassembly of obsolete products is critical for remanufacturing, recycling and recycling. However, existing disassembly studies have few or no resource constraints, such as limited numbers of disassembly operators and tools. Two-stage disassembly model is used to improve the flexibility to adapt to remanufacturing market demand. Based on existing references, this paper establishes a multiobjective two-stage disassembly model based on two-stage data envelopment analysis (two-stage DEA). The resource-constructed two-stage DEA model in this paper fully considers the dynamic configuration information of the output factors in each stage. To avoid the problem where the overall efficiency is optimal, the research constructs a resource constrained efficiency two-stage disassembly model. First, with the goal of minimum disassembly time, economy, energy consumption and environment, this study proposes eNSGA-II. By using mixed mutation and ecological evolution strategies, a well-distributed noninferior solution set is obtained. Second, the group of 16 disassembly schemes is used as decision-making units (DMUs) of the two-stage DEA. A comparison with Chen's model rankings shows that the model in this paper performs better. DMU6 has the highest efficiency ranking, which is the best disassembly solution. Finally, the effectiveness of the proposed algorithm is verified by examples. Compared with NSGA-II and SPEA-II, eNSGA-II shows better performance and effectiveness.

With a reduction in mortality rates of children under 5 years, in low- and middle-income countries, the responsibility to provide quality care to the increased number of surviving children becomes essential. Many of these children present with developmental delay and the onus inevitably rest on the healthcare system. There is, therefore, the need for recognising timely intervention as routine care for these children, who may have potential for a better quality of life with intervention. The authors advocate for early referral and intervention, and provide a brief overview of a holistic approach to developmental delay in low resourced settings from their perspective. [ABSTRACT FROM AUTHOR]

With a reduction in mortality rates of children under 5 years, in low- and middle-income countries, the responsibility to provide quality care to the increased number of surviving children becomes essential. Many of these children present with developmental delay and the onus inevitably rest on the healthcare system. There is, therefore, the need for recognising timely intervention as routine care for these children, who may have potential for a better quality of life with intervention. The authors advocate for early referral and intervention, and provide a brief overview of a holistic approach to developmental delay in low resourced settings from their perspective.

The range and severity of developmental delays vary, and a systematic approach to ensuring early detection for early intervention is essential. The formative years are considered critical for nurturing and maximising developmental potential. In this article, the authors describe a clinical approach to developmental delay within resource-constrained environments of South Africa. The article unpacks the history and examination, developmental screening, surveillance and diagnostic assessment and social determinants of health. For timely interventions to occur, early and accurate assessment is necessary. Medical officers and other health professionals such as nurses, general practitioners and therapists working in low-resourced contexts may use this information in their approach to the assessment of developmental delay.

Prefabricated buildings are the direction of the future development of the construction industry and have received widespread attention. The effective execution of prefabricated construction project scheduling should consider resource constraints and the supply arrangement of prefabricated components. However, the traditional construction resource-constrained project scheduling implementation method cannot simultaneously consider the characteristics of the linkage between component production and on-site assembly construction. It cannot also fully adapt to the scheduling implementation method of the prefabricated construction projects. It is difficult to work out a reasonable project schedule and resource allocation table. In order to determine the relevant schedule parameters that can reflect the actual construction situation of the prefabricated building and meet the scheduling requirements of the prefabricated project, this study proposes a prefabricated construction project scheduling model that considers project resource constraints and prefabricated component supply constraints. Additionally, it improves the design of traditional genetic algorithms (GAs). Research results of the experimental calculation and engineering application show that the proposed project scheduling optimization model and GA are effective and practical, which can help project managers in effectively formulating prefabricated construction project scheduling plans, reasonably allocating resources, reducing completion time, and improving project performance. [ABSTRACT FROM AUTHOR]

Project scheduling has a critical function for many companies. Although there is a vast literature dedicated to the development of solution methodologies, the real-life applications of those techniques are few and often require over-simplification of the real-life problem. This study deals with the implementation of a project scheduling routine for a "make-to-order" machinery manufacturer. Although the problem is very similar to a resource-constrained project scheduling problem (RCPSP), which is a well-known and well-studied problem in the literature, it has multi-project and multi-mode components which make the project planning more challenging. Because of the multi-dimensional complexity of the problem, it is called a "Rich Project Scheduling Problem". Our approach employs two techniques to deal with the issue of complexity. The first one is regarding calculation of the latest start time for each activity in the project. The second one is the decomposition method that includes breaking down the big problem into small manageable pieces. The approach was tested on real-life problems of a machine-building company. We also built more complex test cases from the real projects for testing purposes. Our approach produced high-quality solutions to the complex project scheduling problems within reasonable time limits. This work contributes to current research in several ways. An extension to the RCPSP formulation to include multi-project and multi-mode problems is introduced and successfully used for solving real-life problems. Additionally, activities of an RCPSP can be split into multiple sub-activities. Doing so is called preemption. The proposed formulation permits mode-switching during the execution of an activity, and it uses an alternative methodology to calculate latest activity start times. [ABSTRACT FROM AUTHOR]

The range and severity of developmental delays vary, and a systematic approach to ensuring early detection for early intervention is essential. The formative years are considered critical for nurturing and maximising developmental potential. In this article, the authors describe a clinical approach to developmental delay within resource-constrained environments of South Africa. The article unpacks the history and examination, developmental screening, surveillance and diagnostic assessment and social determinants of health. For timely interventions to occur, early and accurate assessment is necessary. Medical officers and other health professionals such as nurses, general practitioners and therapists working in low-resourced contexts may use this information in their approach to the assessment of developmental delay. [ABSTRACT FROM AUTHOR]

Cryptographic cores integrated with self-test ability fulfill both data security and reliability requirements of the Internet of Things (IoT) network. However, from the IoT perspective where most devices are resource constrained, a fundamental problem associated with most of the self-test architectures is high hardware overhead due to the additional circuit for self-test operation. This paper presents the design of a low-cost self-test architecture and its integration with the PRESENT cipher core. The hardware overhead of the proposed low-cost self-test architecture is reduced by adopting two key strategies: 1) using hardware-efficient X-Compactor technique for test response compaction and 2) reusing the PRESENT cipher core as a Test Pattern Generator (TPG). The proposed self-test architecture is implemented on different Xilinx Field Programmable Gate Array (FPGA) platforms and devices. Analysis of the implementation results shows that the proposed self-test method occupies 23% less hardware area overhead and provides 14% higher throughput per slice performance with the fault coverage of over 99% compared with the existing self-test designs. The resulting analysis indicates that the proposed self-test design is one of the most viable testing solutions for resource-constrained IoT devices.

Goal: The issue of resource allocation is a major concern for project engineers in the scheduling process of a project. Resources over-allocation are often seen in practice after the scheduling of a project, which makes scheduling unhelpful. Modifying an over-allocated schedule is very complicated and requires a lot of effort and time. Besides, during the scheduling process of resource-constrained projects in the constructing companies, managers should concern more than one objective at the same time. This research aims to propose a new heuristic algorithm for minimizing project completion time, cost or maximizing quality of execution of activities simultaneously while multi-mode activities are taken into consideration. Design / Methodology / Approach: In this research, a new heuristic method is proposed for solving multi-objective scheduling problem for multi-mode resource constrained project scheduling problems (MRCPSPs) where the aim is maximizing the net present value (NPV) of project, minimize completion time and maximize the quality of executing activities simultaneously and along with emerging the uncertainty of resources availability and activity durations. The proposed method is then coded by Matlab® 2016. Results: The outcomes of solving small, medium and large scale case studies, the following results achieved: (i) the algorithm could solve all problems in different circumstances with no difficulties; (ii) the large scale problems (with 200 activities, 20 resources and 3 execution modes for each activity) could be solved in 4.43 seconds. (iii) in none of the studied cases over-allocation problem. The proposed method can be considered among the fastest scheduling algorithms found in the literature. In addition, it is found that makespan, NPV and quality have co-relation must be taken into consideration during the scheduling process. Limitations of the investigation: The main limitations of this research is that it only covers resource constrained project scheduling. Moreover, risk factors associated with the objectives of this research have yet to be addressed in future research studies. Practical implications: The performance of the algorithm is validated by using 24 series of dataset that are found in the literature. In order to verify its performance in real practice, it has been applied for a part of a construction project in Malaysia. The outcomes indicated that the algorithm scheduled the problem with 23 activities, 5 constrained resources and 2 execution modes in less than a second and with no over-allocations. The proposed multi-objective algorithm allows the project managers to consider NPV, completion time and quality of activities while scheduling a multi-mode project. In practice, this algorithm can provide a better atmosphere for managers while they aim to consider more than one objective during the scheduling process. Originality / Value: The proposed algorithm is original and can be of great value for future studies and managers in preventing resource over-allocation during the scheduling of multi-objective multi-mode resource constraint project scheduling. Moreover, it can help project managers to find near optimum solutions for complex multi-objective resource constraint projects faster and also with more accuracy.

Goal: The issue of resource allocation is a major concern for project engineers in the scheduling process of a project. Resources over-allocation are often seen in practice after the scheduling of a project, which makes scheduling unhelpful. Modifying an over-allocated schedule is very complicated and requires a lot of effort and time. Besides, during the scheduling process of resource-constrained projects in the constructing companies, managers should concern more than one objective at the same time. This research aims to propose a new heuristic algorithm for minimizing project completion time, cost or maximizing quality of execution of activities simultaneously while multi-mode activities are taken into consideration. Design / Methodology / Approach: In this research, a new heuristic method is proposed for solving multiobjective scheduling problem for multi-mode resource constrained project scheduling problems (MRCPSPs) where the aim is maximizing the net present value (NPV) of project, minimize completion time and maximize the quality of executing activities simultaneously and along with emerging the uncertainty of resources availability and activity durations. The proposed method is then coded by Matlab® 2016. Results: The outcomes of solving small, medium and large scale case studies, the following results achieved: (i) the algorithm could solve all problems in different circumstances with no difficulties; (ii) the large scale problems (with 200 activities, 20 resources and 3 execution modes for each activity) could be solved in 4.43 seconds. (iii) in none of the studied cases over-allocation problem. The proposed method can be considered among the fastest scheduling algorithms found in the literature. In addition, it is found that makespan, NPV and quality have co-relation must be taken into consideration during the scheduling process. Limitations of the investigation: The main limitations of this research is that it only covers resource constrained project scheduling. Moreover, risk factors associated with the objectives of this research have yet to be addressed in future research studies. Practical implications: The performance of the algorithm is validated by using 24 series of dataset that are found in the literature. In order to verify its performance in real practice, it has been applied for a part of a construction project in Malaysia. The outcomes indicated that the algorithm scheduled the problem with 23 activities, 5 constrained resources and 2 execution modes in less than a second and with no over-allocations. The proposed multi-objective algorithm allows the project managers to consider NPV, completion time and quality of activities while scheduling a multi-mode project. In practice, this algorithm can provide a better atmosphere for managers while they aim to consider more than one objective during the scheduling process. Originality / Value: The proposed algorithm is original and can be of great value for future studies and managers in preventing resource over-allocation during the scheduling of multi-objective multi-mode resource constraint project scheduling. Moreover, it can help project managers to find near optimum solutions for complex multi-objective resource constraint projects faster and also with more accuracy. [ABSTRACT FROM AUTHOR]

Digital initiatives are known to support service delivery and citizen engagement, however effective implementation is limited in resource-constrained municipalities in South Africa. One prevalent reason is the lack of a well-articulated strategy to guide deployment, as well as knowledge on how to develop them contextually. This paper uses design science and Weick's theorizing approach to develop a systems-oriented E-government strategy formulation framework at local government level, for a digital citizen engagement initiative called Project X. The strategy formulation process became fundamental in engaging stakeholders and mapping for the effective operation of the digital initiative. [ABSTRACT FROM AUTHOR]

An important component in critical chain project management is a scheduling methodology to support resource constraints. Given task duration estimates and precedence relations along with resource designation for each task, one seeks to adhere to a target due date as well as to shorten the estimated makespan. Key are two types of time buffers to absorb potential delays accumulated from preceding tasks, and this makes the problem complex and hard to solve. The "good enough" strategy has been prevalent in research, focusing on the development of heuristic solution methods. There has been only one attempt to minimize estimated makespan, wherein discrete algebra is utilized. The method is, however, inflexible as you must compose a search space. Even the slightest extension requires a major recast of the approach. Hence, we develop a new approach to find an exact optimal solution in an efficient manner. Given a project instance, an optimization problem is constructed as a mixed-integer linear-program, for which an exact solution can be found using an off-the-shelf solver. While the problem is NP hard, larger-scale project instances, including up to 30 tasks, can be solved within a practical time standard. Extension with respect to resource assignment is easily accomplished. Experimental results highlight the significance of the developed framework. [ABSTRACT FROM AUTHOR]

Background: The limited involvement of audiologists in occupational noise-induced hearing loss (ONIHL) management through hearing conservation programmes (HCPs) is a global issue. In low- and middle-income (LAMI) countries such as South Africa, this is also exacerbated by demand versus capacity challenges. Tele-audiology is an option requiring serious deliberation by the audiology community within HCPs in LAMI contexts. Objectives: This scoping review explores if tele-audiology has a potential value in HCPs and reviews what has been documented in the literature on the use of tele-audiology in HCPs. Method: A scoping review was conducted using the Arksey and O’Malley’s framework. A search was conducted in five electronic bibliographic databases including Science Direct, PubMed, Scopus Medline, ProQuest and Google Scholar and the grey literature to identify publications presenting considerations around tele-audiology in the implementation of HCPs. Results: Findings revealed significant dearth of evidence specific to the use or application of tele-audiology in ONIHL and/or HCPs both within the African context and internationally, despite the purported potential benefit of this service delivery model, particularly in resource-constrained contexts such as LAMI countries. Of the publications deemed potentially relevant to this scoping review, none were found that specifically investigated or addressed the use of tele-audiology in ONIHL or HCPs as their main objective. Nuanced analysis of publications revealed that in the last decade, indication for potential growth in the use of tele-audiology within occupational audiology is indicated. Conclusion: Because of the significant demand versus capacity challenges in LAMI countries, and because of the need for scaling up audiology professionals’ management of HCPs, careful consideration of teleaudiology as a platform to deliver services in these contexts is required.

The growing awareness about the adverse effects of fossil fuels and the ensuing pollution has encouraged and promoted the use of renewable energies throughout the world. This in turn has encouraged governments and investors to show more interest in generation of renewable energy through construction of facilities such as wind farms. The novelty of this research work is the budget constraints consideration for the first time in wind energy projects. This work is done for the Khorasan provinces of Iran. This study is based on regional and municipal data pertaining to the year 2016, and uses the fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method to deal with the uncertainty of the data. The fuzzy TOPSIS method is used to evaluate and rank the candidate cities, and the results are then used to develop a budget-constrained model by fuzzy linear programming with the Maxmin objective function. The resulting mathematical model is optimised with GAMS software. The modelling results show that in the presence of budget constraints, of 10 Khorasan cities considered as candidate locations, Afriz, Rudab, and Fadashk exhibit the best conditions for the construction of wind farms.

Background: Hemophilia is underdiagnosed in India, and there is lack of state specific data on the extent and morbidity. This article provides the real world demographic and clinical data of patients with hemophilia (PwH) in a resource-constrained setting in Punjab, India. Patients and Methods: This is a retrospective analysis of PwH in the institutional hemophilia registry over 9 years. Eligible patients who had a confirmed diagnosis at our institute were included in the analysis. Demographic, clinical, and treatment data used in the current analysis were extracted from medical records using a standardized data collection form. Results: A total of 211 patients were from Punjab, comprising 175 PwH A (91.3%) and 36 with PwH B for uniformity. The mild, moderate, and severe hemophilia in the cohort were 32 (15.1%), 45 (21.3%), and 132 (62.5%), respectively. No patient was on continuous prophylaxis. Inhibitors were positive in 7.9% of patients. Joint deformity was found in 83.5% of severe PwH. Transfusion-transmitted infections were found in 24 (18.3%). There were no statistically significant differences between hemophilia A and B groups with regard to demographic or clinical characteristics. The current median age of the group was 22 years against a national average of 27.6 years. Only 7.4% of the estimated cases of PwH are diagnosed in Punjab. Conclusion: There are significant underdiagnoses, increased incidence of transfusion-transmissible infection, and joint deformity among PwH in Punjab. Therefore, it warrants an immediate need to develop a registry, increase awareness about hemophilia, and provide comprehensive care.

Earlier studies of educational effectiveness in resource-constrained countries tended to focus on fiscal and material resources. However, the impact thereof can be limited where effective processes at the school and classroom levels are not present. Using hierarchical linear modelling, this study draws on SACMEQ data to generate an effective education model for resource-constrained countries, using Uganda as a case study. Rasch modelling was used to construct the educational process indicators, and the dynamic model of educational effectiveness provided the basis for the conceptual framework used. On adjusting for confounding variables, the factors that significantly predicted both mathematics and reading outcomes included opportunity to learn (OTL), school management competences, school–community relationships, and school-based HIV/AIDS support. The effect of teacher academic and professional capital (TAPC) was mediated by OTL. The study argues for refocused attention on the school and teaching processes as key to enhancing educational effectiveness in resource-constrained countries. [ABSTRACT FROM AUTHOR]

RPL is a routing layer protocol for IPv6 low-power lossy wireless networks. The lack of a strong security protection mechanism and running on resource-constrained IoT devices make it vulnerable to network attacks. When performing intrusion detection, it is necessary to minimize the consumption of device resources. Against the above question, this paper analyzed the network topology structure of RPL, the intrusion detection technology of RPL and the principle of common network attacks. Then, this paper expounded and proposed an adaptive energy-saving algorithm. It could reduce equipment power and network load. Finally, this paper implemented the algorithm and verified the effectiveness by Contiki3. 0 and Cooja. Simulation experiments show that the algorithm can select effective detection nodes according to the network topology and reduce the average power of the devices by about 12% with the same true positive rate. [ABSTRACT FROM AUTHOR]

Prefabricated buildings are the direction of the future development of the construction industry and have received widespread attention. The effective execution of prefabricated construction project scheduling should consider resource constraints and the supply arrangement of prefabricated components. However, the traditional construction resource-constrained project scheduling implementation method cannot simultaneously consider the characteristics of the linkage between component production and on-site assembly construction. It cannot also fully adapt to the scheduling implementation method of the prefabricated construction projects. It is difficult to work out a reasonable project schedule and resource allocation table. In order to determine the relevant schedule parameters that can reflect the actual construction situation of the prefabricated building and meet the scheduling requirements of the prefabricated project, this study proposes a prefabricated construction project scheduling model that considers project resource constraints and prefabricated component supply constraints. Additionally, it improves the design of traditional genetic algorithms (GAs). Research results of the experimental calculation and engineering application show that the proposed project scheduling optimization model and GA are effective and practical, which can help project managers in effectively formulating prefabricated construction project scheduling plans, reasonably allocating resources, reducing completion time, and improving project performance.

This paper introduces a comprehensive framework that elucidates the microfoundations of data-driven antimicrobial stewardship programs (ASPs), specifically focusing on resource-constrained settings. Such settings necessitate the utilization of available resources and engagement among multiple stakeholders. The microfoundations are conceptualized as interlinked components: input, process, output, and outcome. Collectively, these components provide a comprehensive framework for understanding the development and implementation of data-driven ASPs in resource-constrained settings. It underscores the importance of considering both the social and material dimensions when evaluating microbiological, clinical, and social impacts. By harmonizing technology, practices, values, and behaviors, this framework offers valuable insights for the development, implementation, and assessment of ASPs tailored to resource-constrained environments.