Distinct Criteria Research Articles

Challenges of Heritage Management in China: A Case Study of Overplanning in Dimen Village

China has 12 different heritage protection systems, which may result in multiple systems regulating and planning for a single heritage site. This study focuses on Dimen village, which is protected under three different systems, and examines five plans collected during fieldwork in 2019 and 2022 to analyze the varying contents of these protection systems. The findings revealed that distinct value assessment criteria for heritage sites exist across different protection systems, leading to differences in how protection areas are demarcated, key focuses established, and methods of utilization implemented. Furthermore, the study highlights the lack of necessary continuity between previous and subsequent plans within frequent planning cycles, which often results in limited implementation. In addition, this study emphasizes the low level of participation by local residents in the planning process and argues for the improvement of this aspect to ensure the effective implementation and preservation of heritage sites.

Tracing the disc: The novel qualitative morphometric MRI based disc degeneration classification system.

This study aimed to develop a classification system for lumbar disc degeneration using routine magnetic resonance images (MRIs) that is easily applicable and unaffected by existing classifications' limitations, and to compare its reliability, reproducibility, and discriminative power to the widely used Pfirrmann classification. Five features were graded. This new classification system has eight grades, with at least one of these five features altering each grade. The T2-weighted sagittal images were acquired using a rapid spin-echo sequence with a repetition time of 2680 to 4900 milliseconds, an echo time of 100 to 109 milliseconds, and an echo train length of 17. Slice thick was 4 mm and the display field of view was 32 × 32 cm. The new classification system used five features: signal intensity, disc height, disc boundary regularity, and nucleus annulus separation. Increased signal intensity, decreased height, decreased regularity, and decreased nucleus-annulus separation indicated degeneration. Four raters classified 400 discs from 80 patients using the Pfirrmann and Novel systems. Statistical analyses were conducted to investigate reliability and correlation. The overall ICC and kappa values were found to be higher in the novel classification. (0.988 indicating excellent agreement for ICC and 0.76/0.94 indicating good-very good agreement for kappa). The Kendall tau c value, which shows the correlation between the two classifications and indicates the validity of the new classification, was 0.872, which is very strong. Through the use of cross-tabulations, the discriminatory power of the two newly added classification criteria was determined. This study demonstrates the intra-rater and inter-rater reliability of an easy-to-use, discriminative novel morphometric MRI based classification system for lumbar disc degeneration. The differentiation of grades based on five distinct criteria may generate novel hypotheses regarding treatment selection and response monitoring, as well as new insights into the study of disc degeneration.

A finite failure software reliability model using extended log-logistic distribution

Software reliability engineering has been developed to examine software systems over the years. Non-homogeneous Poisson process (NHPP) models are widely employed for analyzing software reliability data, as they have the ability to describe the expected number of failures over time using the mean value function. In addition, these models have an intensity function representing the failure rate over time. This article proposes a new non-homogeneous Poisson process model based on extended log-logistic (NHPP ELL) distribution with three parameters. The model properties were derived and represented graphically. Furthermore, the maximum likelihood estimation method was utilized to estimate the model parameters, which were computed numerically using the Newton–Raphson method. Three real software reliability datasets were utilized to evaluate the performance of the new NHPP ELL model based on three distinct criteria: the mean square error, the coefficient of determination (R2), the Theil statistic, the predictive-ratio risk, and the predictive power. Moreover, a comparative study was conducted between the proposed model and several well-known NHPP models regarding goodness-of-fit and predictive performance. All the evaluation measures indicate that the proposed model outperforms the other models across all the considered datasets. In addition, the graphical plots depicting the actual data and the prediction results for all the fitted models show that the proposed model performs well in all three considered software reliability datasets compared to other models.

Deep Convolutional Neural Network Compression based on the Intrinsic Dimension of the Training Data

Selecting the optimal deep learning architecture for a particular task and dataset remains an ongoing challenge. Typically, this decision-making process involves exhaustive searches for neural network architectures or multi-phase optimization, which includes initial training, compression or pruning, and fine-tuning steps. In this study, we introduce an approach utilizing a deep reinforcement learning-based agent to dynamically compress a deep convolutional neural network throughout its training process. We integrate the concept of the intrinsic dimension of the training data to provide the agent with insights into the task's complexity. The agent employs two distinct ranking criteria, L1-norm-based and attention-based measures, to selectively prune filters from each layer as it determines necessary. In the experiments, we used the CIFAR-10 dataset and its subsets (2-class and 5-class subsets) to model the task complexity and showed that the agent learns different policies depending on the intrinsic dimension. The agent, on average, pruned off 78.48%, 77.9%, and 83.12% filters from all the layers of VGG-16 network for CIFAR-10 full, 5-class, and 2-class subsets respectively.

Sub-disciplines in management sciences: criteria of sub-division in theory and research practice

Abstract This paper aims to identify the key criteria for distinguishing sub-disciplines in management sciences and evaluate their application in national and international science classifications. Documents from 16 different countries and areas were studied semantically. Triangulation was used to study 16 sub-discipline classifications and survey expert opinions among 31 representatives of management sciences from Poland and China to achieve the paper’s purpose. Based on the results, the classifications use various criteria for categorising sub-disciplines, with the key criteria being (1) resources, (2) activity areas, (3) management concepts and methods, and (4) types of organisations. Meanwhile, the extent of their use is well in line with the expectations of the management sciences community representatives participating in the survey. The paper proposes a theoretical framework of 13 distinguishing criteria and characterises 16 classifications of sub-disciplines in management science from different countries. The theoretical considerations provide a good insight into the logic of creating a classification of sub-disciplines. They also provide a better description and understanding of the role of research specialisations in building the identity, organisation, and development of the management sciences community. The results align with a discussion on improving the classifications of management sciences’ sub-disciplines. They are essential in identifying future and promising research specialisations within management sciences. They are helpful in the process of reviewing and/or placing particular research issues or problems in specific sub-disciplines of management sciences.

Reconfiguring the Customer Service Domain: Perspectives of Managers, Conversational Designers, and Human Agents on Human–Chatbot Collaboration

This study explored the criteria for evaluating human–chatbot collaboration in customer service using the socio-technical systems theory. Interviews with 28 customer service managers, conversational designers, and human agents revealed their evaluation criteria diverged. Managers prioritized the chatbot’s technical capabilities and preferred a standalone customer service chatbot, while conversational designers prioritized the social aspect, focusing on the chatbot as a support tool for human agents and customers. Human agents mainly evaluated the chatbot as a means to increase job satisfaction. These distinct criteria highlight the importance of an aligned approach in human–chatbot collaboration. To improve this collaboration, integrating the chatbot into customer data systems was suggested.

A Hybrid Approach for Sustainable and Resilient Farmer Selection in Food Industry: Tunisian Case Study

This paper presents an innovative approach for supplier selection (SS) within the Tunisian dairy industry, with a specific focus on sustainability and resilience. The proposed method is a hybrid model that integrates multi-criteria decision-making (MCDM) with fuzzy logic. Initially, twelve distinct criteria are identified, categorized into social, environmental, economic, and resilience indexes through a combination of literature review and expert input. To establish the importance of these criteria, a fuzzy analytic hierarchy process (FAHP) is employed to calculate their weights. These weights are then integrated into a new method called fuzzy multi-attribute border approximation area comparison (FMABAC) to rank the suppliers. The methodology aims to provide decision-makers with a more intuitive means of expressing their preferences and evaluating supplier criteria, ultimately identifying the most effective dairy farmers. The research concludes by evaluating the results through two sensitivity analyses: one involving varying criteria weights and the other involving a comparative assessment with alternative fuzzy MCDM techniques.

Evolutionary U-Net for lung cancer segmentation on medical images

Patients with lung cancer can only be diagnosed and treated surgically. Early detection of lung cancer through medical imaging could save numerous lives. Adding advanced techniques to conventional tests that offer high accuracy in diagnosing lung cancer is essential. U-Net has excelled in diversified tasks involving the segmentation of medical image datasets. A significant challenge remains in determining the ideal combination of hyper parameters for designing an optimized U-Net for detailed image segmentation. In our work, we suggested a technique for automatically generating evolutionary U-Nets to detect and segregate lung cancer anomalies. We used three distinct datasets, namely the LIDC-IRDC Dataset, Luna 16 Dataset, and Kaggle Dataset, for training the proposed work on lung images. Our results, examined with six distinct evaluation criteria used for medical image segmentation, consistently demonstrated the highest performance. More specifically, the GA-UNet outperforms conventional approaches in terms of an impressive accuracy rate of 97.5% and a Dice similarity coefficient (DSC) of 92.3%.

The Discrete Taxonomic Classification of Soils Subjected to Diverse Treatment Modalities and Varied Fertility Grades Utilizing Machine Olfaction

Soil classification stands as a pivotal aspect in the domain of agricultural practices and environmental research, wielding substantial influence over decisions related to real-time soil management and precision agriculture. Nevertheless, traditional methods of assessing soil conditions, primarily grounded in labor-intensive chemical analyses, confront formidable challenges marked by substantial resource demands and spatial coverage limitations. This study introduced a machine olfaction methodology crafted to emulate the capabilities of the human olfactory system, providing a cost-effective alternative. In the initial phase, volatile gases produced during soil pyrolysis were propelled into a sensor array comprising 10 distinct gas sensors to monitor changes in gas concentration. Following the transmission of response data, nine eigenvalues were derived from the response curve of each sensor. Given the disparate sample counts for the two distinct classification criteria, this computational procedure yields two distinct eigenspaces, characterized by dimensions of 112 or 114 soil samples, each multiplied by 10 sensors and nine eigenvalues. The determination of the optimal feature space was guided by the “overall feature information” derived from mutual information. Ultimately, the inclusion of random forest (RF), multi-layer perceptron (MLP), and multi-layer perceptron combined with random forest (MLP-RF) models was employed to classify soils under four treatments (tillage and straw management) and three fertility grades. The assessment of model performance involved metrics such as overall accuracy (OA) and the Kappa coefficient. The findings revealed that the optimal classification model, MLP-RF, achieved impeccable performance with an OA of 100.00% in classifying soils under both criteria, which showed almost perfect agreement with the actual results. The approach proposed in this study provided near-real-time data on the condition of the soil and opened up new possibilities for advancing precision agriculture management.

Research on low‐velocity impact resistance of carbon fiber composite laminates

AbstractThis research conducts a comprehensive experimental and numerical analysis of carbon fiber composite laminates under low‐velocity impact conditions. Split Hopkinson Pressure Bar (SHPB) was employed to conduct impact testing on laminates with two layup sequences ( and ) under impacts ranging from 2 to 6 J. For assessing damage in laminates, a comprehensive progressive damage model and a simplified model were developed. The primary distinction between these models lies in the fact that the former incorporates the strengthening effect of compression on the delamination behavior, while the latter does not. Both models produce a good agreement with experimental results in terms of force–time, force–displacement curves, and absorbed energies. However, notable differences were noted in the predicted internal damage; the simplified model was underpredicted in terms of damage size and distribution compared to the comprehensive progressive damage model.Highlights Impact tests were conducted on and composites. In order to simulate damage caused by impacts in laminates, an energy‐based damage model was created, and cohesive elements were utilized to model interlaminar delamination. The strengthening effect of compression was explored. Distinct damage criteria were established for two cases. Damage detection of composites by x‐rays.

Privacy preserving unique identity generation from multimodal biometric data for privacy and security applications

AbstractThis study presents a novel approach for generating unique identities from multi‐modal biometric data using ensemble feature descriptors extracted from the consistent regions of fingerprint and iris images. The method employs prominent feature selection and discriminant vector generation to enhance intra‐class similarity and inter‐class separability. Finally, a novel quantization mechanism is used to generate a unique identity. This identity might be vulnerable to many attacks. A shielding mechanism is proposed to address this issue. Experimental results substantiate the method's efficacy, satisfying criteria for distinctiveness, randomness, revocability, and irreversibility. Security analyses showcase resilience against diverse attacks, establishing its applicability in forensic investigations, digital wallets, remote authentication, and other privacy‐focused applications. The confidential UID generation scheme ensures privacy and security without involving biometric data or UID enrollment, enhancing its suitability across various applications.

Structured request form in musculoskeletal radiology examinations (CONCERTO): results of an expert Delphi consensus-structured radiology request form for correct classification of patients to undergo radiological examinations of the Italian Society of Medical and Interventional Radiology (SIRM), the Italian Society of Rheumatology (SIR) and the Italian Society of Orthopedics and Traumatology (SIOT).

To describe a Delphi consensus for the realization of a structured radiology request form for patients undergoing musculoskeletal imaging. A steering committee (four radiologists, a rheumatologist and an orthopedic surgeon) proposed a form to an expert panel (30 members, ten radiologists, ten rheumatologists and ten orthopedic surgeons). Through an online survey, the panelists voted on their level of agreement with the statements of the form using a 10-point Likert scale (1: no agreement; 10: total agreement) in a three-round process. A combination of two distinct criteria, a mean agreement level ≥ 8 and a percentage of at least 75% of responses with a value ≥ 8, was deemed as acceptable. The form achieved high median ratings in all the assessed key features. During the first round, all items met the threshold to be advanced as unmodified in the next round. Additional proposed items were considered and introduced in the next round (six items in Section 1, five items in Section 2, ten items in Section 3, 11 items in Section 4, six items in Section 5, eight items in Section 6, ten items in Section 7 and eight items in Section 8). Of these items, in round 3, only six reached the threshold to be integrated into the final form. Implementation of a structured radiology request form can improve appropriateness and collaboration between clinicians and radiologists in musculoskeletal imaging.

Association of mesenteric lymphadenitis with abdominal pain in children – A case–control study

Background: Enlarged mesenteric lymph nodes (MLNs) are a frequent ultrasonography finding in children with abdominal pain. Studies have shown that the incidence of enlarged mesenteric lymph nodes varies widely from 14% to 86%. The site, size, and number of lymph nodes are the distinguishing criteria for abnormal lymphadenopathy from normal lymph nodes. Aims and Objectives: The aims and objectives of the study are to estimate the prevalence of mesenteric lymphadenitis in children aged 4–15 years, who have abdominal pain with age and sex-matched controls without abdominal pain. Materials and Methods: The study was conducted after getting approval from the Institutional Ethics Committee. The MLN of all sizes was evaluated and measured using an ultrasound abdomen. Age and gender-matched controls were included in the study. Children with MLN were divided into 2 groups based on the size of the lymph nodes. (group A-MLN <4 mm and group B MLN >4 mm). In some cases, the site and size of MLN were noted and correlated with the severity of abdominal pain. Results: The ultrasonogram of the abdomen revealed that 15 (22.7%) cases had ≤4 mm nodes and 38 (57.6%) had >4 mm nodes. Out of the 38 cases, 2 (3.8%) had >10 mm nodes. Among the controls, 16 (24.2%) had ≤4 mm, 8 (12.1%) had >4 mm nodes, and none had MLN >10 mm. The odds ratio (OR) of cases having mesenteric lymphadenitis over controls was 5.067 (OR=5.067). Conclusion: Based on the results of our study, mesenteric lymphadenopathy >4 mm is associated with abdominal pain in children aged 4–15 years.

Fitness trade-offs of multidrug efflux pumps in Escherichia coli K-12 in acid or base, and with aromatic phytochemicals.

Multidrug efflux pumps are the frontline defense mechanisms of Gram-negative bacteria, yet little is known of their relative fitness trade-offs under gut conditions such as low pH and the presence of antimicrobial food molecules. Low pH contributes to the proton-motive force (PMF) that drives most efflux pumps. We show how the PMF-dependent pumps AcrAB-TolC, MdtEF-TolC, and EmrAB-TolC undergo selection at low pH and in the presence of membrane-permeant phytochemicals. Competition assays were performed by flow cytometry of co-cultured Escherichia coli K-12 strains possessing or lacking a given pump complex. All three pumps showed negative selection under conditions that deplete PMF (pH 5.5 with carbonyl cyanide 3-chlorophenylhydrazone or at pH 8.0). At pH 5.5, selection against AcrAB-TolC was increased by aromatic acids, alcohols, and related phytochemicals such as methyl salicylate. The degree of fitness cost for AcrA was correlated with the phytochemical's lipophilicity (logP). Methyl salicylate and salicylamide selected strongly against AcrA, without genetic induction of drug resistance regulons. MdtEF-TolC and EmrAB-TolC each had a fitness cost at pH 5.5, but salicylate or benzoate made the fitness contribution positive. Pump fitness effects were not explained by gene expression (measured by digital PCR). Between pH 5.5 and 8.0, acrA and emrA were upregulated in the log phase, whereas mdtE expression was upregulated in the transition-to-stationary phase and at pH 5.5 in the log phase. Methyl salicylate did not affect pump gene expression. Our results suggest that lipophilic non-acidic molecules select against a major efflux pump without inducing antibiotic resistance regulons.IMPORTANCEFor drugs that are administered orally, we need to understand how ingested phytochemicals modulate drug resistance in our gut microbiome. Bacteria maintain low-level resistance by proton-motive force (PMF)-driven pumps that efflux many different antibiotics and cell waste products. These pumps play a key role in bacterial defense by conferring resistance to antimicrobial agents at first exposure while providing time for a pathogen to evolve resistance to higher levels of the antibiotic exposed. Nevertheless, efflux pumps confer energetic costs due to gene expression and pump energy expense. The bacterial PMF includes the transmembrane pH difference (ΔpH), which may be depleted by permeant acids and membrane disruptors. Understanding the fitness costs of efflux pumps may enable us to develop resistance breakers, that is, molecules that work together with antibiotics to potentiate their effect. Non-acidic aromatic molecules have the advantage that they avoid the Mar-dependent induction of regulons conferring other forms of drug resistance. We show that different pumps have distinct selection criteria, and we identified non-acidic aromatic molecules as promising candidates for drug resistance breakers.

Differences in the composition of the crime provided for by art. 201-2 (illegal use of humanitarian aid) from related elements of crime

In connection with the increase in the scale of humanitarian aid and persons who cynically profit from charitable activities, disregarding the norms of morality, the Criminal Code of Ukraine was supplemented with a new Art. 201-2 of the Criminal Code of Ukraine, which establishes criminal liability for the illegal use of humanitarian aid, charitable donations or free aid for other purposes than the intended purpose, namely for profit or personal enrichment, where the object of the encroachment will be public relations in the field of use of humanitarian aid goods, charitable donations or free aid. The above has actualized the need to consider the differences between the corpus delicti under Art. 201-2 of the Criminal Code of Ukraine and some related corpus delicti. The author establishes that the main criterion for distinction is the subject matter, namely, humanitarian aid, charitable donations and free-of-charge assistance. In addition, the object and the objective side are also distinguished. The object of a criminal offense under Art. 201-2 of the Criminal Code of Ukraine is relations in the field of economic activity, unlike crimes with a similar objective party, in which the object is the right of ownership as a legally protected interest, which is expressed in the possession, use and disposal of property. At the same time, since the object of Art. 201­2 of the CC is relations in the sphere of economic activity, the main criterion for measuring the gravity of a criminal offense is the total cost of items that should be received by recipients of humanitarian aid, charitable donations, free assistance, and, for example, under Art. 192 of the CC - the amount of property damage to the owner of property caused by the illegal use of such property. At the same time, the illegal use of humanitarian aid is different from the crime under Art. 191 of the Criminal Code of Ukraine in the context of the sale of humanitarian aid, which means the paid transfer of property by one person to another person, since the embezzlement of another’s property requires the free transfer of another’s property in favor of another person. It is concluded that the acts prohibited by Art. 201-2 of the Criminal Code of Ukraine, in its absence, would be covered by criminal offenses against property.

Fracture analysis of Brazilian circular hole disk under mixed mode loading

The paper presents an investigation into a Brazilian disk specimen featuring a concentric circular hole, accompanied by two internal edge radial cracks. By introducing rotations of the cracks relative to the vertical axis, a combination of fracture modes I and II is induced. Employing the finite element method, we compute stress intensity factors related to fracture modes I and II, alongside T-stresses, while varying geometric parameters such as inner and outer diameters, crack length-to-ring width ratio, and crack inclination angle. Experimental analyses of ebonite's fracture toughness in the mixed mode are conducted, subjecting samples to static loading until complete failure. Each test provides the angle at which crack initiation occurs and the corresponding critical load. Three distinct fracture criteria - the generalized maximum tangential stress criterion (GMTS), extended maximum tangential strain criterion (EMTSN), and generalized strain energy density (GSED) criterion - are employed to predict fracture direction and critical load. The outcomes exhibit good correspondence between experimental critical loads and theoretical predictions.

Identification of Criteria for Enabling the Adoption of Sustainable Maintenance Practice: An Umbrella Review

The evolution from traditional industrial maintenance to sustainable maintenance (SM) is pivotal within an existing industrial ecosystem. This study, utilising an umbrella review (UR), critically examines this transition, highlighting its increased importance in maintenance decision-making (MDM). Using a sample (n = 20) of reviews, we synthesised meta-, methodological-, and content-based evidence and performed bibliometric, thematic and statistical analyses. For the bibliometric and thematic/conceptual analyses, we used the R bibliometrix package. The results show that the early research focuses mainly on theoretical aspects, while recent studies examine the practical implications. Also, comprehensive studies evaluating the benefits of implementing environmental and social aspects within MDM are still lacking. For that reason, we switched the attention to content-based data, from which we identified 43 distinct criteria discussed. For the analysis of criteria, the Bayesian Network Analysis with Gaussian Copula Graphical Model (BNA-GCGM) method was used. Although the evidence shows that environmental pollution, energy consumption and health and safety of workers are the most discussed criteria, the BNA-GCGM suggests that labour costs, resource consumption, employee satisfaction and energy consumption, among others, are the most influential criteria in the network analysis. Interestingly, after distinguishing studies into pre- and post-2021 research, the results show that pre-2021 research is primarily focused on economic and technical factors, reflecting a profit-oriented approach. The post-2021 analysis suggests a discernible shift towards more balanced considerations by incorporating social and environmental factors, suggesting a more socially responsible approach. Finally, while SM is gaining momentum, further empirical and practical research are required to demonstrate the advantages that SM offers in the light of the upcoming Industry 5.0.

Developing a Comprehensive List of Criteria to Evaluate the Characteristics and Quality of eHealth Smartphone Apps: Systematic Review.

The field of eHealth is growing rapidly and chaotically. Health care professionals need guidance on reviewing and assessing health-related smartphone apps to propose appropriate ones to their patients. However, to date, no framework or evaluation tool fulfills this purpose. Before developing a tool to help health care professionals assess and recommend apps to their patients, we aimed to create an overview of published criteria to describe and evaluate health apps. We conducted a systematic review to identify existing criteria for eHealth smartphone app evaluation. Relevant databases and trial registers were queried for articles. Articles were included that (1) described tools, guidelines, dimensions, or criteria to evaluate apps, (2) were available in full text, and (3) were written in English, French, German, Italian, Portuguese, or Spanish. We proposed a conceptual framework for app evaluation based on the dimensions reported in the selected articles. This was revised iteratively in discussion rounds with international stakeholders. The conceptual framework was used to synthesize the reported evaluation criteria. The list of criteria was discussed and refined by the research team. Screening of 1258 articles yielded 128 (10.17%) that met the inclusion criteria. Of these 128 articles, 30 (23.4%) reported the use of self-developed criteria and described their development processes incompletely. Although 43 evaluation instruments were used only once, 6 were used in multiple studies. Most articles (83/128, 64.8%) did not report following theoretical guidelines; those that did noted 37 theoretical frameworks. On the basis of the selected articles, we proposed a conceptual framework to explore 6 app evaluation dimensions: context, stakeholder involvement, features and requirements, development processes, implementation, and evaluation. After standardizing the definitions, we identified 205 distinct criteria. Through consensus, the research team relabeled 12 of these and added 11 more-mainly related to ethical, legal, and social aspects-resulting in 216 evaluation criteria. No criteria had to be moved between dimensions. This study provides a comprehensive overview of criteria currently used in clinical practice to describe and evaluate apps. This is necessary as no reviewed criteria sets were inclusive, and none included consistent definitions and terminology. Although the resulting overview is impractical for use in clinical practice in its current form, it confirms the need to craft it into a purpose-built, theory-driven tool. Therefore, in a subsequent step, based on our current criteria set, we plan to construct an app evaluation tool with 2 parts: a short section (including 1-3 questions/dimension) to quickly disqualify clearly unsuitable apps and a longer one to investigate more likely candidates in closer detail. We will use a Delphi consensus-building process and develop a user manual to prepare for this undertaking. PROSPERO International Prospective Register of Systematic Reviews CRD42021227064; https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021227064.

Tourmaline as an indicator for pegmatite evolution and exploration: A case study from the Chakabeishan deposit, northeastern Tibetan Plateau

To assess the potential of tourmaline as an indicator for pegmatite evolution and exploration, we measured and compared the geochemical compositions in tourmalines of the barren, Be-rich and Li-rich pegmatites from the Chakabeishan (CKBS) deposit, eastern North Qaidam Tectonic Belt, northeastern Tibetan Plateau. Two types of tourmalines from the barren pegmatites are identified: optically homogeneous fine-grain tourmalines (H-Tur) and optically zoned coarse-grain tourmalines (OZ-Tur). Both H-Tur and OZ-Tur are of magmatic origin, showing high Na/(Na + Ca) (0.961–0.990), YAl (0.389–0.757 apfu) and low Mg/(Fe + Mg) (0.085–0.230). The core-to-rim δ11B increase within H-Tur and OZ-Tur, together with the enrichment of 11B from H-Tur (crystallized earlier) to OZ-Tur, indicates that fluids were unsaturated in the evolution of barren pegmatites. Compared to H-Tur and OZ-Tur, tourmalines from the Be- and Li-rich pegmatites show higher Nb/Sc (>3:4) and lower Mn/Zn (<1:1), Mn/Li (<3:1), and Sc/Li (<1:500), which are useful indirect criteria of distinction between the fertile and the barren pegmatites. The reliable tourmaline geochemical criteria for further distinguishing the Li-rich from the Be-rich pegmatites are Pb/Sr < 0.11, Nb/Sr < 0.15, and Pb/Co < 4. A compilation suggests that diagrams of (V + Sr)-(Li + Zn), Li-Zn/Sr, Sn/10Nb-Li-100Nb, and Zn/Sn-Li/10Sc-5Sc could discriminate tourmalines of granite-related pegmatite-type Li deposits from those of other deposits and rocks, showing implications for determining prospective areas for further Li-rich pegmatite exploration by using tourmalines recovered from surface sediments.

Unified optimality criteria for the Target–Attacker–Defender game

The game consists of two teams, team A (Attacker) and team T/D (Target and Defender). The Attacker aims to minimise the separation between itself and the Target at time t f ; and team T/D aims to maximise the separation distance. Previous works in the literature identified three distinct optimality criteria to characterise the state-feedback Nash equilibrium. We introduce a new unifying paradigm given by the Critical Escape Trajectories Theorem, which simultaneously characterises the Target's escape set and the value function of the game in all regions, highlighting a deep underlying geometric connection between the differential game of kind and the differential game of degree. Leveraging previous results in the literature, the Critical Escape Trajectories Theorem is proved to be equivalent and is utilised to develop an efficient algorithm for the computation of the state-feedback Nash equilibrium.