Miracle-dz/UniFAR-FTUs huggingface dataset:
A Lightweight Trust Mechanism with Attack Detection for IoT

In this paper, we propose a lightweight and adaptable trust mechanism for the issue of trust evaluation among Internet of Things devices, considering challenges such as limited device resources and trust attacks. Firstly, we propose a trust evaluation approach based on Bayesian statistics and Jøsang’s belief model to quantify a device’s trustworthiness, where evaluators can freely initialize and update trust data with feedback from multiple sources, avoiding the bias of a single message source. It balances the accuracy of estimations and algorithm complexity. Secondly, considering that a trust estimation should reflect a device’s latest status, we propose a forgetting algorithm to ensure that trust estimations can sensitively perceive changes in device status. Compared with conventional methods, it can automatically set its parameters to gain good performance. Finally, to prevent trust attacks from misleading evaluators, we propose a tango algorithm to curb trust attacks and a hypothesis testing-based trust attack detection mechanism. We corroborate the proposed trust mechanism’s performance with simulation, whose results indicate that even if challenged by many colluding attackers that can exploit different trust attacks in combination, it can produce relatively accurate trust estimations, gradually exclude attackers, and quickly restore trust estimations for normal devices.
Biodegradable Zn−1wt.%Mg(−0.5wt.%Mn) Alloys: Influence of Solidification Microstructure on Their Corrosion Behavior

The development of biodegradable Zn-based alloys for implants that effectively mimic the functionality of native bone throughout the healing process is a multifaceted challenge; this is particularly evident in the task of achieving appropriate corrosion rates. This work explores the incorporation of 0.5wt. %Mn into a Zn−1wt. %Mg alloy, with focus on the relationship between corrosion behavior and microstructure. Electrochemical corrosion tests were carried out in a 0.06 M NaCl solution using as-solidified samples with two distinct microstructural length scales. Mn addition was found to induce significant electrochemical active behavior. Localized corrosion was predominant in interdendritic regions, with the ternary alloy exhibiting a higher susceptibility. For both alloys, the coarsening of the microstructure promoted a slight inclination to accelerate the corrosion rates in both biodegradable Zn alloys. The corrosion rate showed an increase of about nine-times with Mn addition for coarser eutectic spacings, while for finer ones, the increase was by about 22 times.
Time, Space and Social Change in Rural Pakistan: An Ethnographic Study of Jhokwala Village, Lodhran District

This thesis is a study of the social organisation of time and space in a Pakistani village. The fieldwork was carried out in Jhokwala Village, Lodhran District through 2010. A rapid population growth in the second half of the last century resulted in an inadequate supply of agricultural land, leading to a gradual shift from an agricultural to the market economy. Many farmers are abandoning agriculture and entering wage labour. This combined with urbanisation, more pervasive telecommunication services, the media, and technological changes has affected shifts in the ways of perceiving and managing time and space. In this thesis, I examine generational changes in the village. There have been generational shifts in the types of calendars and the contexts for which they are used. Household organisation and composition have also undergone dramatic change as a consequence of economic transformations. Fundamental economic changes have included a number of shifts in how people engage with information technologies, the media, and urbanisation. These have resulted in a transformation of the physical layout of the village along with changes in the design and structure of places such as the mosque and the house. Such changes in the physical environment have also triggered a shift in the sociospatial relationships, which has resulted in negotiation of some social boundaries between different gender and social classes. I examine the ways in which changes in the social organisation of time and space are indicative of the pace, direction and mechanism of social change.
Paradoxical association between body mass index and in-hospital mortality in elderly patients with chronic obstructive pulmonary disease in Japan

Background and objective: The prevalence and mortality of chronic obstructive pulmonary disease (COPD) in elderly patients are increasing worldwide. Low body mass index (BMI) is a well-known prognostic factor for COPD. However, the obesity paradox in elderly patients with COPD has not been well elucidated. We investigated the association between BMI and in-hospital mortality in elderly COPD patients. Methods: Using the Diagnosis Procedure Combination database in Japan, we retrospectively collected data for elderly patients (  65 years) with COPD who were hospitalized between July 2010 and March 2013. We performed multivariable logistic regression analysis to com-pare all-cause in-hospital mortality between patients with BMI of  18.5 kg/m 2 (underweight), 18.5–22.9 kg/m 2 (low–normal weight), 23.0–24.9 kg/m 2 (high–normal weight), 25.0–29.9 kg/m 2 (overweight), and  30.0 kg/m 2 (obesity) with adjustment for patient backgrounds. Results: In all, 263,940 eligible patients were identified. In-hospital mortality was 14.3%, 7.3%, 4.9%, 4.3%, and 4.4%, respectively, in underweight, low–normal weight, high–normal weight, overweight, and obese patients. Underweight patients had a significantly higher mortality than low–normal weight patients (odds ratio [OR]: 1.55, 95% confidence interval [CI]: 1.48–1.63), whereas lower mortality was associated with high–normal weight (OR: 0.76, CI: 0.70–0.82), overweight (OR: 0.73, CI: 0.66–0.80), and obesity (OR: 0.67, CI: 0.52–0.86). Higher mortality was significantly associated with older age, male sex, more severe dyspnea, lower level of consciousness, and lower activities of daily living. Conclusion: Overweight and obese patients had a lower mortality than low–normal weight patients, which supports
Grazing activity of Clibanarius corallinus (H. Milne Edwards, 1848) (Decapoda: Anomura: Diogenidae) on epilithic algae in Australian coral reefs

Following an incidental observation of captive Clibanarius corallinus (H. Milne Edwards, 1848) supposedly removing algae from each other’s shells, we conducted a feeding experiment over 72 hours to understand its potential role as a mesograzer in coral reef ecosystems. Epiphyte-covered, coral rubble fragments of Acropora spp. were exposed to hermit crab (N = 41) activity for 72 h in a flow-through seawater aquarium system at Heron Island, southern Great Barrier Reef, Australia to understand whether hermit crabs could remove epilithic algae and if so, to what extent. Coral fragments exposed to the hermit crabs had 9.1% less chlorophyll at the end of the experiment. The detritus generated in the experimental set-up had 2.4 times more chlorophyll and 33.4% less organic biomass than the detritus generated in the control environment. The crabs did on average lose 0.11 g of their initial weight, which could have been a consequence of the experimental set-up. These results suggest that C. corallinus has the potential to contribute to the control of epilithic algae in coral reefs, with such effect having hitherto been overlooked as a result of the cryptic behaviour of this hermit crab species.
Exploring Hop Varieties with Discriminating Flavan-3-ol Profiles Likely to Improve Color and Colloidal Stability of Beers

While the Saaz aromatic variety remains classified as a total-flavanoid-rich cultivar, no inverse correlation was found between total flavanoids and the α-acid content when the dual-purpose varieties Citra, CTZ, Amarillo, Eureka! , Mandarina Bavaria, Mosaic, Polaris, and Sabro were considered. The levels of hop flavan-3-ol monomers, dimers, and trimers (quantitated by HPLC-MS/MS) appeared strongly influenced by variety and harvest year. On the other hand, the catechin/epicatechin ratio (and B3/B2 ratio) proved stable within the same variety through two successive harvest years. Among the nine herein-investigated varieties, Citra and Saaz displayed notable catechin/epicatechin ratios (>3.7 compared to <1.6 for the others), whereas Polaris exhibited the lowest monomer content (less than 800 mg/kg). These distinctive profiles could impact the colloidal and color stability of hop-forward beers.
Identification of immunotherapy biomarkers for improving the clinical outcome of homologous recombination deficiency patients with lung adenocarcinoma

Homologous recombination deficiency (HRD) is a common molecular signature of genomic instability and has been shown to be a biomarker for targeted therapies. However, there is a lack of studies on the role of HRD changes in lung adenocarcinoma (LUAD) transcriptomics. HRD scores were determined using single nucleotide polymorphism (SNP) array data from LUAD patients from The Cancer Genome Atlas (TCGA) database. Transcriptional data from patients with different scores were analyzed to identify biomarkers associated with HRD. Candidate biomarkers were validated using Gene Expression Omnibus (GEO)-sourced datasets and an immunotherapy cohort. According to the bulk transcriptome and clinical characteristics of 912 LUAD patients and Single-cell RNA-seq of 9 LUAD patients from TCGA and GEO databases, we observed increased MS4A6A expression in HRD tumors; high MS4A6A expression predicted improved survival outcomes. Furthermore, a comprehensive analysis of the tumor immune microenvironment (TIME) revealed a positive correlation between MS4A6A expression and neoantigen loading and immune cell infiltration. Additionally, the immunotherapy cohort confirmed the possibility of using MS4A6A as a biomarker. Collectively, we suggest that MS4A6A is associated with HRD and provide a new perspective toward identifying promising biomarkers for immunotherapy.
Speculative/philosophical modeling of measurement for comprehending modern OCT imaging

Modern conception of Optical Coherence Tomography (OCT) measurement covers a wide range of measurement acts from photo-detection to Artificial-Intelligence (AI) based diagnosis. Here the measurement targets may include the structure, optical properties, tissue (by image processing and segmentation), and disease (by computer-aided diagnosis). Despite recent rapid expansion of the measurement targets, there is not theoretical (speculative) model to comprehend such wide spectrum of the measurement acts. Here we present a new speculative (theoretical) modeling of optical measurement, so-called “epistemological metrology model. ” We use this model to critically understand several modern extensions of Optical Coherence Tomography (OCT), such as computer-aided diagnosis, Degree-of-Polarization-Uniformity (DOPU) imaging, and Attenuation-Coefficient (AC) imaging.
Automation of the single-track study for L-PBF additive manufacturing processes (for AlSi10Mg powder)

When using a new powder material in each individual selective laser melting unit, the process engineer has to conduct process development works (PDW) to find the optimal combination of process parameters. The results of the PDW are analysed manually by the process engineer without the use of process decision support tools. Due to the expanding technological capabilities of the equipment and the available range of material properties, the possible set of parameters is also expanding, complicating the already non-trivial process of searching for printing process parameters. In order to reduce the PDW time, in this paper we proposed a rapid analysis tool to select individual experimental results with single welded tracks of AlSi10Mg powder. The process of conducting the experiment on domestic equipment was reviewed and the efficiency of the automation tool was investigated in comparison with the traditional manual selection approach. It is concluded that it is possible to apply the developed tool for materials and installations of additive manufacturing not considered in the study.
Many Central American hummingbirds can be aged and sexed by molt patterns and bill corrugations

We document molt extent; age-specific molt patterns, plumages, and percent of the bill with corrugations; the presence or absence of delayed plumage maturation and bill color changes in males of some species; and molt timing in the 19 resident hummingbird species of Belize. Molt strategies and rates of bill smoothing were similar to North American species, with all species showing limited to partial preformative molts, replacing only body feathers and some wing coverts and retaining all remiges and rectrices. Extent of bill corrugations reduced to ≤10% of bill length in all species by the time definitive cycle basic plumage is achieved. Males in sexually dichromatic species showed delayed maturation in plumage characteristics and/or bill coloration, and in two dichromatic species some older females showed male-like plumage. Nine species representing multiple clades showed advanced timing to the second prebasic molt, indicating that this trait may be a proximal response to individuals not breeding during the first molt cycle. Species with advanced second prebasic molts replaced fewer wing coverts during the preformative molt than species with later molt timing.
Jasmonates disrupt carrageenan synthesis during carposporogenesis in the red seaweed Grateloupia imbricata

In this study, we monitored changes in cell wall sulfated galactans in the red seaweed Grateloupia imbricata after the rapid (48 h) induction of cystocarp maturation and carpospore development by the volatile hormone methyl jasmonate (MEJA). Synthesis of sulfated galactans, carrageenans, which requires sulfated UDP galactose, was followed by expression analysis of genes encoding phosphoglucomutase (PGM), galactose-1-phosphate uridyltransferase (GALT), and those responsible for sulfate assimilation (S-transporter and sulfate adenylyltransferase, SAT). In addition, the expression of carbohydrate sulfotransferase and galactose-6-sulfurylase responsible for the addition and removal of sulfate groups to the galactans backbone were evaluated. Structural changes, such as thallus softening, were analyzed using Fourier-transformed infrared spectroscopy (FTIR) spectra, and ploidy was assessed using flow cytometry. The results showed downregulation of most of the genes encoding precursors or those in charge of transformation into sulfated hexoses for cell wall synthesis. Furthermore, alterations in the FTIR spectrum of carrageenan from MEJA-induced fertile thalli, such as the disappearance and flattening of absorption bands, were observed. The promptness of these events and the ploidy of thalli and spores seem to confirm the induction of mitotic production of haploid spores by MEJA.
Hollywood’s Racial Order and the Re-throning of White Supremacist Identity

Released during a period of heightened racial tension over the impact of racism in the United States and Europe, the 2021 films Stillwater and Dune Part One reveal the pervasiveness of Arab Muslim misrepresentations in Hollywood and the subtilty of white supremacist ideology as it re-emerges in new cinematic productions. With many symbolic and pronounced references to the delusions of the “great replacement” theory, the foundational blueprint of white supremacist identity in both stories, this article contends that these films recentre whiteness to either villainise Arab Muslims or totally erase them. Stillwater disguises the stereotypes on which Arab racialisation is predicated by embedding them in the details of a subplot. Dune, by contrast, is set in an imaginary Arab space with no Arabs, and yet portrayals of Arabs and Islam are front, and centre and it imagines a world with fierce but “generic” coloured people serving their great white leaders.
UvA-DARE ( Digital Academic Repository ) Synthesis , sorting , and processing into distinct isoforms of human macrophage chitotriosidase Renkema

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Reliability assessment of two‐level balanced systems with common bus performance sharing subjected to epistemic uncertainty

Two‐level balanced systems with common bus performance sharing (TLBS‐CBPS), represented by power battery systems, play an important role in various industries. Where the two‐level balance refers to when the system is unbalanced, redistributing performance between modules using a common bus for the intermodule balance, followed by the in‐module component performance redistribution to achieve global balance, that is, the performance differences among all components are within the balance degree threshold. However, the component performance has epistemic uncertainty due to measurement limitations, and the distance‐dependent transmission loss incurs during the performance redistribution. These problems make the reliability evaluation of TLBS‐CBPS challenging. To address these issues, a reliability evaluation method for TLBS‐CBPS is proposed by considering two‐level balance, epistemic uncertainty, and transmission loss. First, the system model is constructed from working modes, and the two‐level rebalancing process is described as three nonlinear programming problems. Then, based on the Dempster–Shafer evidence theory, the belief universal generating function (BUGF) method is proposed to evaluate the uncertainty of the system reliability. To improve the computation efficiency, a simplified BUGF algorithm is given through merging, judging, labeling, and expanding realizations. Finally, two examples of lithium‐ion battery packs demonstrate the effectiveness of the proposed method.
A new approach to overcoming resistance to immunotherapy: nanotechnology

Immunotherapy for immune response has ushered in a new era of cancer treatment. In recent years, new immunotherapeutic agents have been introduced into clinical trials and even approved for marketing. However, the widespread use of immunotherapeutic agents faces an unavoidable challenge: immunotherapy does not work at all for some patients, or has good efficacy in the initial phase, but immunotherapy resistance develops within a short period of time, and immunotherapy can also cause serious adverse effects such as autoimmune inflammation and non-specific inflammation. How to enable patients to overcome drug resistance, reduce the toxic side effects of drugs, enhance patient compliance and improve patient survival has become a problem that clinicians have to face. The advent of nanotechnology provides an encouraging platform for immunotherapy. It can not only improve the bioavailability and stability of drugs and reduce toxic side effects, but also reduce resistance to immunotherapy. Here, we discuss these research advances and discuss potential challenges and future directions.
Generalized Predictive Control for $LC$-Filtered Voltage-Source Inverters With Enhanced Predictive Horizon

Generalized predictive control (GPC) for power converter applications provides the benefits of constant switching frequency, explicit stability check, and high control bandwidth. However, featuring the second-order characteristic in the $LC$-filtered voltage source inverter, the assessment and investigation of GPC as the inner control loop have not been fully fulfilled, especially under the grid-connected mode. Besides, the inherent ability of GPC enables the prediction of future system behavior within longer horizons, which, however, has been rarely investigated and, thus, it is still unclear about the closed-loop property brought by the enhanced predictive horizons. To this end, this work first clarifies the contribution of adopting GPC by comparing it to the capacitor-voltage control+inductor-current feedback active damping with optimal damping coefficient design, where the virtual synchronous generator is used to implement the case study. Through the simulation and experimental results, the GPC expresses a smoother and faster dynamic process and enhanced transient frequency nadir compared to the existing multiloop strategy. The robustness and stability are analyzed through the closed-loop eigenvalue, and it is also revealed that the GPC achieves stronger robustness against the variation of the control and plant parameters simultaneously by increasing the prediction horizon length.
Distributed multiple step ahead prediction considering communication delays

Prediction is an essential part of predictive control and is widely applied in control engineering. In a distributed control system configuration, there are signal transmissions between local subsystems. Communication delays impose a limit on the achievable prediction performance. Even though there is a plethora of literatures available for multiple step ahead prediction under the centralised framework, they are traditional techniques that cannot be applied to the distributed framework due to the interactions between the different subsystems and communication delays that have not been taken into account. In this study, a technique for determining the distributed multiple step ahead prediction is proposed which is optimal in sense of the lowest total prediction error variance. The proposed approach is useful for designing optimal controllers or assessing the performance of the implemented control loop while the controller structure has the distributed framework.
Reinforcement learning optimized digital twin based synthetic data generation for defect detection of titanium spacer

In the field of automatic defect detection, one of the major challenges for training accurate classifiers using supervised learning is the insufficient and limited diversity of datasets. Obtaining an adequate amount of image data depicting defective surfaces in an industrial setting is costly and time-consuming. Furthermore, the collected dataset may suffer from selection bias, resulting in underrepresentation of certain defect classes. This research aims to tackle the issue of surface defect detection in titanium metal spacer rings by introducing a novel approach that leverages a digital twin framework. The behavior of the digital representation is optimized using a reinforcement learning algorithm. Subsequently, the optimized digital twin is utilized to generate synthetic data, which is then employed to train a spacer defect detection classifier. The performance of this classifier is evaluated using real-world data. The results illustrate that the model trained with synthetic data outperforms the one trained on a limited amount of real data. This work emphasizes the potential of digital twin-based synthetic data generation and reinforcement learning optimization in enhancing spacer surface defect detection and addressing the data scarcity challenge in the field. When the generated synthetic data and real data combined is used to train inspection network, the inspection background accuracy reaches 93.07% and defect detection accuracy reaches 94.2% surpassing the defect detection performance of inspection network trained only using real data.