Miracle-dz/UniFAR-FTUs huggingface dataset:
A Multi-constraint and Multi-objective Allocation Model for Emergency Rescue in IoT Environment

Emergency relief operations are essential in disaster aftermaths, necessitating effective resource allocation to minimize negative impacts and maximize benefits. In prolonged crises or extensive disasters, a systematic, multi-cycle approach is key for timely and informed decision-making. Leveraging advancements in IoT and spatio-temporal data analytics, we've developed the Multi-Objective Shuffled Gray-Wolf Frog Leaping Model (MSGW-FLM). This multi-constraint, multi-objective resource allocation model has been rigorously tested against 28 diverse challenges, showing superior performance in comparison to established models such as NSGA-II, IBEA, and MOEA/D. MSGW-FLM's effectiveness is particularly notable in complex, multi-cycle emergency rescue scenarios, which involve numerous constraints and objectives. This model represents a significant step forward in optimizing resource distribution in emergency response situations.
Analysis of Microarray Gene Expression Data

Microarrays provide the biological research community with tremendously rich, sensitive and detailed information on gene expression profiles. Gene expression profiling and gene expression patterns have been found useful for solving a wide variety of important biological and biomedical problems, including the study of metabolic pathways, inference of the functions of unknown genes, diagnosis of diseased states, as well as facilitating the development of individualized drug treatments through pharmacogenomics. Given the significant impact of microarray gene expression data in biological and biomedical research, this breakthrough technology urgently needs the assistance of advanced computational methods for interpreting and utilizing the raw information. This paper reviews several main research directions and methods in the analysis of microarray gene expression data.
Mutant p53R270H gain of function phenotype in a mouse model for oncogene‐induced mammary carcinogenesis

In human breast cancer, mutations in the p53 gene are associated with poor prognosis. However, analysis of patient data so far did not clarify, whether missense point mutations in the p53 gene, in addition to causing loss of wild‐type p53 function, also confer a gain of function phenotype to the encoded mutant p53. As heterogeneity of patient material and data might obscure a clear answer, we studied the effects of a coexpressed mutant p53R270H in transgenic mice in which SV40 early proteins initiate the development of mammary adenocarcinoma (WAP‐T mice). In such tumors the endogenous wild‐type p53 is functionally compromised by complex formation with SV40 T‐antigen, thereby constituting a loss of wild‐type p53 function situation that allowed analysis of the postulated gain of function effects of mutant p53R270H. We found that mutant p53R270H in bi‐transgenic mice enhanced the transition from intraepithelial neoplasia to invasive carcinoma, resulting in a higher frequency of invasive carcinoma per gland and per mouse, a more severe tumor phenotype, and more frequent pulmonary metastasis. Surprisingly, mutant p53R270H in this system does not increase genomic instability. Therefore, other postulated gain of function activities of mutant p53 must be responsible for the effects described here. © 2007 Wiley‐Liss, Inc.
Cloning of the Bovine Immunodeficiency Virusgag Gene and Development of a Recombinant-Protein-Based Enzyme-Linked Immunosorbent Assay

ABSTRACT An enzyme-linked immunosorbent assay (ELISA) was established for the rapid detection of specific bovine immunodeficiency virus (BIV) antibodies in cattle, using recombinant Gag protein as an antigen. Thegag coding region from BIV was cloned into an expression vector, pQE32, which expressed high levels of recombinant protein fromEscherichia coli. The ELISA was standardized by a checkerboard titration against known BIV-positive and -negative sera from cattle and a monoclonal antibody to the Gag protein. A total of 139 cattle serum samples, from the diagnostic laboratory at Kansas State University, Manhattan, and from the Dairy Station, Louisiana State University, Baton Rouge, were compared by ELISA and immunoblot assays for the detection of BIV-specific antibodies. Of 26 cattle sera samples which tested positive using the immunoblot assay, 23 were positive by ELISA, thus establishing a strong correlation between the two tests. The sensitivity and specificity of ELISA relative to immunoblotting were 0.88 and 0.93, respectively. ELISA proved to be as specific as immunoblotting but was much less time-consuming and easier to perform.
Leader–Member Relationship and Burnout: The Moderating Role of Leader Integrity (领导�?�?员关系与下属工作倦怠：领导正直的调解作用)

English Abstract: In this study, we propose and test the idea that a strong relationship between leader and follower will be associated with the subordinate's burnout. We base the study on the leader–member exchange framework (LMX), resource exchange theory, and the job demands–resources model of burnout, and conceptualize that a strong LMX is associated with burnout in two ways: high LMX involves high job demands, which lead to exhaustion; low LMX involves low job resources, which leads to cynicism. We propose that the relationship between LMX and the two forms of burnout will be stronger when the leader is perceived to be low on moral integrity. Using a survey of 218 employees, we find support for the hypotheses. Implications for future research and managerial practices are discussed. Chinese Abstract: 本研究提出并检验了领导下属关系与下属工作倦怠之间的关系。 基于领导－成员交换理论、资源交换理论，以及工作倦怠模型，本研究提出领导－成员关系有可能会通过两个途径导致下属的工作倦怠：高水平的领导－成员关系会使下属感知的工作要求过多，进而引起精力耗竭；而低水平的领导－成员关系会使下属感知的工作资源过少，进而可能引起工作冷漠。 本研究进一步提出，当下属感知到领导的道德正直度较低时，上面的两个关系都会更强。 研究以218名员工为样本进行调研，假设得到了检验。 本文最后讨论了该研究结果对未来研究及管理实践的启示。
Micro-checkpointing in fault tolerant runtimes

Multicore processors are increasingly used in safety-critical applications. On one hand, their increasing chip density causes these processors to be more susceptible to transient faults; on the other hand the existence of many cores offers a straightforward compartmentalization against permanent hardware faults. To tackle the first issue and take advantage of the second, we present FT-BDDT, a fault-tolerant task-parallel runtime system. FT-BDDT extends the BDDT runtime system that implements the OMP-Ss dataflow programming model for spawning and scheduling parallel tasks, in which, similarly to OpenMP 4.0, a dynamic dependence analysis detects conicting tasks and automatically synchronizes them to avoid data races and non-determinism. FT-BDDT recovers from both transient and permanent faults. Transient faults during task execution result in simply re-running the task. To handle transient faults in the runtime system, FT-BDDT uses fine-grain micro-checkpointing of the runtime state, so that a recovery is always possible at the level of rerunning a basic block of code on error. Permanent faults are treated in a similar fashion, by having the master core "steal" the task checkpoint or the runtime micro-checkpoint and reschedule the task or recover the runtime state, respectively. We evaluate FT-BDDT on several benchmarks under various error conditions, while guiding errors to attain maximum coverage of the runtime code. We find a 9.5% average runtime overhead for checkpointing, a constant small space overhead, and a negligible recovery time per error.
Assessing the effect of introducing adaptive charging stations in public EV charging infrastructures

The availability of publicly accessible charging stations in urban areas can foster the widespread adoption of Electric Vehicles (EVs). However, the introduction of public charging infrastructures will put an additional strain on the power grid due to the possible occurrence of peak demands. This study is a first attempt to quantitatively assess the potential benefits of introducing in a public charging infrastructure smart charging stations that are capable of modulating the current supplied to the EVs. Specifically, we assume that each charging station has limited power resources that must be shared among the EVs attached to its charging sockets according to a given scheduling strategy. To evaluate the performance of such system we utilise SUMO, an open-source and widely used vehicular traffic simulator, along with a highly realistic mobility trace for the metropolitan area of Luxembourg City. Simulation results indicate that the use of simple charging strategies that take advantage of the modulation capabilities of smart charging stations (e.g., fair-sharing or token-based scheduling approaches) can effectively mitigate the impact of EV charging demands on the power grid with a limited degradation of charging performance. However, our results also confirm that a significant investment on charging infrastructure might be necessary to guarantee a non-blocking charging service.
Preferences in Symmetries and Symmetries in Drawings: Asymmetries between Ages and Sexes

Visual structure in art has been studied by Arnheim [1] and more recently by Leyton [2] who suggests that an analysis of symmetrical structure is fundamental to the understanding of visual structure. Three experiments revealed age and sex differences in symmetry preferences with dot patterns and productions in drawings by children and adults. Asymmetrical patterns were less preferred and seen as less symmetrical with age, while patterns with multiple symmetries [3] showed the opposite effects. Increasingly complex and creative use of symmetries with age were seen in drawings. Greater preference for multiple symmetries in dot patterns by females and more frequent use of bilateral symmetry in drawings by girls and multiple symmetries by women were in contrast to judgments of greater overall symmetry in drawings by males.
Explainable Machine Learning-Based Security and Privacy Protection Framework for Internet of Medical Things Systems

The Internet of Medical Things (IoMT) transcends traditional medical boundaries, enabling a transition from reactive treatment to proactive prevention. This innovative method revolutionizes healthcare by facilitating early disease detection and tailored care, particularly in chronic disease management, where IoMT automates treatments based on real-time health data collection. Nonetheless, its benefits are countered by significant security challenges that endanger the lives of its users due to the sensitivity and value of the processed data, thereby attracting malicious interests. Moreover, the utilization of wireless communication for data transmission exposes medical data to interception and tampering by cybercriminals. Additionally, anomalies may arise due to human errors, network interference, or hardware malfunctions. In this context, anomaly detection based on Machine Learning (ML) is an interesting solution, but it comes up against obstacles in terms of explicability and protection of privacy. To address these challenges, a new framework for Intrusion Detection Systems (IDS) is introduced, leveraging Artificial Neural Networks (ANN) for intrusion detection while utilizing Federated Learning (FL) for privacy preservation. Additionally, eXplainable Artificial Intelligence (XAI) methods are incorporated to enhance model explanation and interpretation. The efficacy of the proposed framework is evaluated and compared with centralized approaches using multiple datasets containing network and medical data, simulating various attack types impacting the confidentiality, integrity, and availability of medical and physiological data. The results obtained offer compelling evidence that the FL method performs comparably to the centralized method, demonstrating high performance. Additionally, it affords the dual advantage of safeguarding privacy and providing model explanation.
What Do Students’ Explanations Look Like When They Use Second-Hand Data?

Explanation studies underlined the importance of using evidence in support of claims. However, few studies have focused on students' use of others' data (second-hand data) in this process. In this study, students collected data from a local water source and then took all the data back to the classroom to create scientific explanations by using claim–evidence–reasoning model on a new mobile application. A middle school science teacher from a Midwest town participated with four sixth-grade classes. After collecting their own data from a local water source, students created explanations by analyzing the data they collected (first-hand data), and by analyzing existing data set collected by another school from another river (second-hand data). By analyzing the health of these two water sources, students created two scientific explanations. Students participating in this study created stronger explanations when analyzing the data they generated (first-hand data).
Digits: freehand 3D interactions anywhere using a wrist-worn gloveless sensor

Digits is a wrist-worn sensor that recovers the full 3D pose of the user's hand. This enables a variety of freehand interactions on the move. The system targets mobile settings, and is specifically designed to be low-power and easily reproducible using only off-the-shelf hardware. The electronics are self-contained on the user's wrist, but optically image the entirety of the user's hand. This data is processed using a new pipeline that robustly samples key parts of the hand, such as the tips and lower regions of each finger. These sparse samples are fed into new kinematic models that leverage the biomechanical constraints of the hand to recover the 3D pose of the user's hand. The proposed system works without the need for full instrumentation of the hand (for example using data gloves), additional sensors in the environment, or depth cameras which are currently prohibitive for mobile scenarios due to power and form-factor considerations. We demonstrate the utility of Digits for a variety of application scenarios, including 3D spatial interaction with mobile devices, eyes-free interaction on-the-move, and gaming. We conclude with a quantitative and qualitative evaluation of our system, and discussion of strengths, limitations and future work.
Leveraging Personalization to Facilitate Privacy

Online social networks have enabled new methods and modalities of collaboration and sharing. These advances bring privacy concerns: online social data is more accessible and persistent and simultaneously less contextualized than traditional social interactions. To allay these concerns, many web services allow users to configure their privacy settings based on a set of multiple-choice questions.We suggest a new paradigm for privacy options. Instead of suggesting the same defaults to each user, services can leverage knowledge of users' traits to recommend a machine-learned prediction of their privacy preferences for Facebook. As a case study, we build and evaluate MyPrivacy, a publicly available web application that suggests personalized privacy settings. An evaluation with 199 users shows that users find the suggestions to be appropriate and private; furthermore, they express intent to implement the recommendations made by MyPrivacy. This supports the proposal to put personalization to work in online communities to promote privacy and security.
Understanding consumers’ creating behaviour in social media: an application of uses and gratifications and the theory of reasoned action

Employing the theory of uses and gratifications in conjunction with the theory of reasoned action, this study examines why consumers create social media content and how their motivational beliefs and subjective norms influence attitudes toward, intention to, and behaviour of creating social media content. By combining qualitative and quantitative analyses, the results identified five significant motivations to create social media content, including social-cognition, entertainment, self-expression, social-belonging, and communication. Structural equation modelling revealed that some motivations were positively related to attitudes toward creating behaviour, which in turn affected intentions and real behaviours involved in creating social media content. However, subjective norms did not prove to be directly influential. The implications of these results are discussed.
Toward a perceptual video-quality metric

The advent of widespread distribution of digital video creates a need for automated methods for evaluating the visual quality of digital video. This is particularly so since most digital video is compressed using lossy methods, which involve the controlled introduction of potentially visible artifacts. Compounding the problem is the bursty nature of digital video, which requires adaptive bit allocation based on visual quality metrics, and the economic need to reduce bit-rate to the lowest level that yields acceptable quality. In previous work, we have developed visual quality metrics for evaluating, controlling,a nd optimizing the quality of compressed still images. These metrics incorporate simplified models of human visual sensitivity to spatial and chromatic visual signals. Here I describe a new video quality metric that is an extension of these still image metrics into the time domain. Like the still image metrics, it is based on the Discrete Cosine Transform. An effort has been made to minimize the amount of memory and computation required by the metric, in order that might be applied in the widest range of applications. To calibrate the basic sensitivity of this metric to spatial and temporal signals we have made measurements of visual thresholds for temporally varying samples of DCT quantization noise.
Detection of Malingered Neurocognitive Dysfunction Among Patients with Acquired Brain Injuries

The Word Memory Test (WMT) is one of the most sensitive forced-choice tests available designed to evaluate negative response bias (NRB). Presently there is no valid verbal test designed to evaluate NRB for Hebrew-speaking patients. The aims of the present study were to validate the response bias measures of the WMT among Hebrew-speaking patients with acquired brain injuries and to reveal the malingering base rate among Israeli patients involved in compensation-seeking. Participants were 112 patients. The Test of Memory Malingering (TOMM) was used for convergent validity and injury related variables were used for concurrent validity. A translated version of the WMT had high split-half reliability. Regarding convergent validity, WMT effort measures had high positive correlations with the TOMM. Moreover, based on TOMM cutoff scores for classification, the WMT had reasonable classification rates. Regarding concurrent validity, multivariate logistic regression revealed that failure in the WMT was significantly.
Model-based feature refinement by ellipsoidal face tracking

We describe a new method to relieve common assumptions/ restrictions in head tracking by using a model-based approach. This improves local feature matching which only considers the pattern around the extracted feature excluding the object shape, so that misalignment can occur. In this paper, to overcome constraints on motion we consider region- and distance-based feature refinement methods to validate the local features used when tracking the ellipsoidal object. We also present a direct mapping method to reconstruct 3D feature positions for tracking. The utility of the new method has been demonstrated for face pose estimation using the Boston face database.
Narrative Interaction in Family Dinnertime Conversations

Reminiscing has been shown to be a critical conversational context for the development of autobiographical memory, self-concept, and emotional regulation (for a review, see Fivush, Haden, & Reese, 2006). Although much past research has examined reminiscing between mothers and their preschool children, very little attention has been given to family narrative interaction with older children. In the present study, we examined family reminiscing in spontaneous narratives that emerged during family dinnertime conversations. The results revealed that mothers contributed more to the narratives than did fathers in that they provided, confirmed, and negated more information, although fathers requested more information than mothers. In exploratory analyses, mothers' contributions to shared family narratives were found to be related to fewer internalizing and externalizing behaviors in their children, while fathers' contributions to individual narratives of day-to-day experiences were related to fewer internalizing and externalizing behaviors in their children. These results indicate that mothers and fathers may play different roles in narrative construction with their children, and there is some suggestion that these differences may also be related to children's behavioral adjustment.
Supporting collaboration in notecards

This paper describes a project underway to investigate computer support for collaboration. In particular, we focus on experience with and extensions to NoteCards, a hypertext-based idea structuring system. The forms of collaboration discussed include draft-passing, simultaneous sharing and online presentations. The requirement that mutual intelligibility be maintained between collaborators leads to the need for support of annotative and procedural as well as substantive activities.
Cultura de Inovação: Conceitos e Modelos Teóricos

This study portrays the state of the art in scientific literature on the culture of innovation, with the objective of characterizing its meaning and especially describing different theoretical models that seek to understand how it occurs in an organizational environment. To enrich the analysis, research results show the relationship between organizational culture and innovation. The literature review was carried out in 2011 using the following databases: Coordination for the Improvement of Higher Education Personnel (CAPES), Proquest and Directory of Open Access Journals (DOAJ). The keywords used were the expression culture of innovation and the joint terms culture and innovation, only full articles were included in the research. Culture of innovation articles that were cited in the papers identified in the literature search were also considered. The analysis consisted of 40 articles, based on the predefined criteria, and showed that this is a topic of interest for researchers in different world regions. It is a complex theme determined by factors with a systemic character. There is a predominance of quantitative research and strong evidence of a relationship between organizational culture and innovation, which requires further research to test the theoretical models proposed by these different authors.
Factorial Validity of Jones and Crandall's Short Index of Self-Actualization

Jones and Crandall (1986) have reported initial psychometric data on the Short Index of Self-actualization. Included in their study was a principal components analysis. The authors reported that the instrument was characterized by four factors and a fifth uninterpretable factor. The present authors submitted the Jones-Crandall model to a confirmatory factor analysis using the confirmatory factor analytic model. The results showed substantial agreement with the Jones-Crandall model—a five-factor model with the fifth considered uninterpretable. The main difference in the findings was in the factor correlations. Jones and Crandall used an orthogonal rotation whereas the present study determined that an oblique solution is more in harmony with the data.