Lysine is an essential amino acid that cannot be synthesized in humans. Rice is a global staple food for humans but has a rather low lysine content. Identification of the quantitative trait nucleotides (QTNs) and genes underlying lysine content is crucial to increase lysine accumulation. In this study, five grain and three leaf lysine content datasets and 4,630,367 single nucleotide polymorphisms (SNPs) of 387 rice accessions were used to perform a genome-wide association study (GWAS) by ten statistical models. A total of 248 and 71 common QTNs associated with grain/leaf lysine content were identified. The accuracy of genomic selection/prediction RR-BLUP models was up to 0.85, and the significant correlation between the number of favorable alleles per accession and lysine content was up to 0.71, which validated the reliability and additive effects of these QTNs. Several key genes were uncovered for fine-tuning lysine accumulation. Additionally, 20 and 30 QTN-by-environment interactions (QEIs) were detected in grains/leaves. The QEI-sf0111954416 candidate gene LOC_Os01g21380 putatively accounted for gene-by-environment interaction was identified in grains. These findings suggested the application of multi-model GWAS facilitates a better understanding of lysine accumulation in rice. The identified QTNs and genes hold the potential for lysine-rich rice with a normal phenotype. Full article

Adequate surgical margins are essential in oral cancer treatment, this is, however, difficult to appreciate during training. With advances in training aids, we propose a silicone-based surgical simulator to improve training proficiency for the ablation of oral cavity cancers. A silicone-based tongue cancer model constructed via a 3D mold was compared to a porcine tongue model used as a training model. Participants of varying surgical experience were then asked to resect the tumors with clear margins, and thereafter asked to fill out a questionnaire to evaluate the face and content validity of the models as a training tool. Eleven participants from the Otolaryngology-Head and Neck Surgery unit were included in this pilot study. In comparison to the porcine model, the silicone model attained a higher face (4 vs. 3.6) and content validity (4.4 vs. 4.1). Tumor consistency was far superior in the silicone model compared to the porcine model (4.1 vs. 2.8, p = 0.0042). Fellows and staff demonstrated a better margin clearance compared to residents (median 3.5 mm vs. 1.0 mm), and unlike the resident group, there was no incidence of positive margins. The surgical simulation was overall useful for trainees to appreciate the nature of margin clearance in oral cavity cancer ablation. Full article

Background/Objectives: Pycnodysostosis is a rare genetic disorder causing skeletal dysplasia. It is determined by a gene mutation leading to cathepsin K deficiency and predisposes a patient to osteosclerosis, resulting in increased bone fragility. The altered bone quality typical of this disease is responsible for an increased risk of fractures. The purpose of our study was to evaluate the orthopedic manifestations and potential pitfalls in the surgical treatments of pathological fractures in a series of patients treated in our institution who were affected by pycnodysostosis. Methods: We retrospectively evaluated clinical and radiographic characteristics of five patients with pycnodysostosis treated for pathological fractures at our hospital in the past 5 years. Results: Two male and three female patients were included in this study. Four patients had a family history of pycnodysostosis. All the patients were of short stature, but only two underwent growth hormone treatment. All the patients experienced fractures, mostly in their lower limbs and occurring as a result of low-energy trauma. Most of the patients experienced either consolidation delay or nonunion. Conclusions: The orthopedic management of fractures in patients with pycnodysostosis poses an ongoing challenge for orthopedic surgeons. The fact that the bone is simultaneously sclerotic and brittle makes any orthopedic surgical treatment challenging and at a high risk of nonunion in any case. Full article

A novel time-domain algorithm is proposed in this paper for the iterative estimation of drive files. A drive file is a synchronized batch of dynamic time series commands that are simultaneously sent to one or more actuators in a test rig that is designed for service environment replication (SER). When drive file commands are input to an SER test rig, the response of the article under test is similar to what was measured in a service environment. The proposed Pulse Train Filtered-X Least Mean Square (PT-Fx-LMS) algorithm is based on methods developed for active noise and vibration control (ANVC). A time-domain PT-Fx-LMS algorithm is shown through several simulation studies to rapidly converge to a dynamic solution in a small number of iterations for a one degree-of-freedom nonlinear suspension. The PT-Fx-LMS algorithm is also shown to enable targeted iteration over isolated time slices within the data set, which challenges conventional frequency-domain techniques. Full article

The presence of vitamin D3 deficiency associated with the presence of metabolic syndrome (MS) has important public health effects. This study aims to investigate the relationship between vitamin D3 deficiency, MS and vitamin D3 receptor (VDR), GC Vitamin D binding protein (GC), and cytochrome P450 family 2 subfamily R member 1 (CYP2R1) gene polymorphisms, and genes whose encoded proteins are responsible for vitamin D3 metabolism and transport. A total of 58 participants were included in this study (age 39 ± 12 years) and were selected over a 12-month period. They were divided into four groups, depending on the presence of polymorphisms in VDR, GC, and CYP2R1 genes and their weight status. At baseline, in months 3, 6, and 12, biochemical parameters including 25(OH)D3, total cholesterol, LDL cholesterol, HDL cholesterol, triglycerides, and homeostatic model assessment (HOMA index), the insulin resistance indicator were measured. Our results show that all subjects in the polymorphism group supplemented with vitamin D3 reached an optimal level of vitamin D3 associated with high concentrations of 25(OH)D3. Weight loss was most significant in patients in the POW group (overweight patients). Full article

This study investigates the production of clausal embeddings by 195 Russian speakers (67 monolingually raised speakers, 68 heritage speakers in the US, and 60 heritage speakers in Germany) in different communicative situations varying by formality (formal vs. informal) and mode (spoken vs. written). Semi-spontaneous data were manually annotated for clause type and analyzed using a binomial generalized mixed-effects model. Our results show that heritage speakers of both groups and monolingually raised speakers behave alike regarding their use of embedded clauses. Specifically, all speaker groups produce embedded clauses more frequently in formal situations compared to informal situations. Mode was not found to influence the production of embedded clauses. This behavior suggests an underlying register awareness in heritage speakers of Russian. Such register awareness might be a result of the high involvement of heritage speakers with Russian. This study contributes to our understanding of linguistic outcomes of heritage speakers and highlights the influence of communicative situations on language production. Full article

Effective fault detection in chemical processes is of utmost importance to ensure operational safety, minimize environmental impact, and optimize production efficiency. To enhance the monitoring of chemical processes under noisy conditions, an innovative statistical approach has been introduced in this study. The proposed approach, called Multiscale Principal Component Analysis (PCA), combines the dimensionality reduction capabilities of PCA with the noise reduction capabilities of wavelet-based filtering. The integrated approach focuses on extracting features from the multiscale representation, balancing the need to retain important process information while minimizing the impact of noise. For fault detection, the Kantorovich distance (KD)-driven monitoring scheme is employed based on features extracted from Multiscale PCA to efficiently detect anomalies in multivariate data. Moreover, a nonparametric decision threshold is employed through kernel density estimation to enhance the flexibility of the proposed approach. The detection performance of the proposed approach is investigated using data collected from distillation columns and continuously stirred tank reactors (CSTRs) under various noisy conditions. Different types of faults, including bias, intermittent, and drift faults, are considered. The results reveal the superior performance of the proposed multiscale PCA-KD based approach compared to conventional PCA and multiscale PCA-based monitoring methods. Full article

Ultrasonic guided wave (UGW) inspection is an emerging non-destructive testing(NDT) technique for rail flaw detection, where weak UGW signals under strong noise backgrounds are difficult to detect. In this study, a UGW signal identification model based on a chaotic oscillator is established. The approach integrates the UGW response into the critical state of the Duffing system to serve as a disturbance control variable. By evaluating the system’s motion state before and after introducing the UGW response, identification of UGW signals can be realized. Thus, the parameters defining the critical state of Duffing oscillators are determined by $K_e$. Moreover, an electromagnetic transducer was specifically devised to enable unidirectional excitation for UGWs targeted at both the rail base and rail head. Experimental studies showed that the proposed methodology effectively detected and located a 0.46 mm notch at the rail base and a 1.78 mm notch at the rail head. Furthermore, $K_e$ was directly proportional to the notch size, which could be used as a quantitative index to characterize the rail flaw. Full article

Topic modelling is a text mining technique for identifying salient themes from a number of documents. The output is commonly a set of topics consisting of isolated tokens that often co-occur in such documents. Manual effort is often associated with interpreting a topic’s description from such tokens. However, from a human’s perspective, such outputs may not adequately provide enough information to infer the meaning of the topics; thus, their interpretability is often inaccurately understood. Although several studies have attempted to automatically extend topic descriptions as a means of enhancing the interpretation of topic models, they rely on external language sources that may become unavailable, must be kept up to date to generate relevant results, and present privacy issues when training on or processing data. This paper presents a novel approach towards extending the output of traditional topic modelling methods beyond a list of isolated tokens. This approach removes the dependence on external sources by using the textual data themselves by extracting high-scoring keywords and mapping them to the topic model’s token outputs. To compare how the proposed method benchmarks against the state of the art, a comparative analysis against results produced by Large Language Models (LLMs) is presented. Such results report that the proposed method resonates with the thematic coverage found in LLMs and often surpasses such models by bridging the gap between broad thematic elements and granular details. In addition, to demonstrate and reinforce the generalisation of the proposed method, the approach was further evaluated using two other topic modelling methods as the underlying models and when using a heterogeneous unseen dataset. To measure the interpretability of the proposed outputs against those of the traditional topic modelling approach, independent annotators manually scored each output based on their quality and usefulness as well as the efficiency of the annotation task. The proposed approach demonstrated higher quality and usefulness, as well as higher efficiency in the annotation task, in comparison to the outputs of a traditional topic modelling method, demonstrating an increase in their interpretability. Full article

An environment that supports lifelong learning contributes to the sustainability of the organisations in a Smart City, their stakeholders and ultimately, the city itself. Workplace Learning Analytics (WLA) can provide an organisation’s employees with the opportunity for lifelong learning in the workplace to enhance their skills and knowledge in their current and/or future roles. It uses the data generated by Learning Experience Platforms (LXPs) and other learning platforms to provide support for data-driven decision-making to gain a competitive edge. One of the components of successful and sustainable WLA is a layered architecture. The purpose of this paper is to present the design of a WLA architecture that can be used in organisations to impact successful WLA. This architecture was developed from the results of evaluating four potentially relevant architectures for WLA. The evaluation consisted of three phases. In the first phase, the architectures were evaluated using the DeLone and McLean Model of Information Systems Success. In the second phase, a real-world case of an organisation that provides lifelong learning opportunities to its stakeholders was used to validate the findings of the first phase. The proposed Layered Architecture for WLA was further validated in the third phase where a focus group discussion was held with participants from the real-world context. The architecture can provide valuable guidance to both practitioners and researchers to improve the success of WLA. Full article

Urban greenery is a strategy to improve the thermal environment in urban areas affected by heat islands and global warming. These phenomena can harm the citizens’ quality of life. Researchers have investigated the thermal benefits of urban vegetation, but only a few have explored its complexities across diverse urban scales. Understanding these variations is critical for precise analysis, customized solutions, efficient resource allocation, and enhancing urban living quality while promoting sustainability and climate resilience. This paper reviews 250 scientific articles about the relationship between greenspace and the urban thermal environment published between 2010 and 2023 through urban scales. It summarizes the parameters and findings of greenery’s contribution to cooling the urban environment. The data reveal that most studies concentrated on the block scale, public open spaces, neighborhoods, parks, grouped vegetation, mixed arrangements, high vegetation, spatial parameters, and the use of air temperature data to report their findings. The cooling-effect evidence shows that the block scale has an average mitigation range of 0.7–2.7 °C, the neighborhood scale of 1.1–2.9 °C, and the city scale of 0.5–2.2 °C. Furthermore, it is critical to define reliable research methods and perform thorough software validation to assess model performance and establish guidelines for urban-landscape design accurately. Full article

In order to conserve valuable soil and water resources and avoid problems related to frozen soil, it is important to study the migration of frozen soil water. A greater understanding of frozen soil–water migration can assist with sustainable development and utilization of soil and water resources in frozen areas. This study used an indoor soil column test device to conduct a one-way indoor freezing test of unsaturated soil and the response of soil sample water migration to different freezing temperatures, initial moisture contents, soil densities, freezing times, solute concentrations, and solute types. The experimental and analytical results showed that the temperature field of the soil sample could be divided into three stages: sharp cooling, slow cooling, and stability. After the soil sample had been frozen for 100 h, the temperature field stabilized. The freezing temperature, initial water content, soil density, and freezing time affected water migration in the soil sample. Lower freezing temperatures and greater initial water content resulted in higher levels of water migration. By contrast, greater soil density led to lower water migration levels. In addition, longer freezing times produced smoother soil–water migration curves. The solute concentration and solute type also affected water migration in frozen soil; the higher the solute concentration, the greater the water migration. Compared with CaCl₂, NaCl had a stronger effect, causing more water migration and leading to a higher water content. The research findings will aid further studies on soil and water utilization, environmental maintenance, and restoration in areas with seasonally frozen soil, as well as promote the sustainable development of agriculture, water conservancy project development, and the social economy. Full article

Fibrosis, a pathological alteration of the repair response, involves continuous organ damage, scar formation, and eventual functional failure in various chronic inflammatory disorders. Unfortunately, clinical practice offers limited treatment strategies, leading to high mortality rates in chronic diseases. As part of investigations into gaseous mediators, or gasotransmitters, including nitric oxide (NO), carbon monoxide (CO), and hydrogen sulfide (H₂S), numerous studies have confirmed their beneficial roles in attenuating fibrosis. Their therapeutic mechanisms, which involve inhibiting oxidative stress, inflammation, apoptosis, and proliferation, have been increasingly elucidated. Additionally, novel gasotransmitters like hydrogen (H₂) and sulfur dioxide (SO₂) have emerged as promising options for fibrosis treatment. In this review, we primarily demonstrate and summarize the protective and therapeutic effects of gaseous mediators in the process of fibrosis, with a focus on elucidating the underlying molecular mechanisms involved in combating fibrosis. Full article

The advancement of an intelligent automobile sound switching system has the potential to elevate the market standing of automotive products, with the pivotal prerequisite being the selection of automobile sounds based on the driver’s subjective perception. The subjective responses of diverse individuals to sounds can be objectively manifested through EEG signals. Therefore, EEG signals are employed herein to attain the recognition of automobile sounds. A subjective evaluation and EEG signal acquisition experiment are designed involving the stimulation of three distinct types of automobile sounds, namely comfort, power, and technology sounds, and a comprehensive database of EEG signals corresponding to these three sound qualities is established. Then, a specific transfer learning model based on a convolutional neural network (STL-CNN) is formulated, where the method of training the upper layer parameters with the fixed bottom weights is proposed to adaptively extract the EEG features related to automobile sounds. These improvements contribute to improving the generalization ability of the model and realizing the recognition of automobile sounds fused with EEG signals. The results of the comparison with traditional support vector machine (SVM) and convolutional neural network (CNN) models demonstrate that the accuracy of the test set of the STL-CNN model reaches 91.5%. Moreover, its comprehensive performance, coupled with the ability to adapt to individual differences, surpasses that of both SVM and CNN models. The demonstrated method in the recognition of automobile sounds based on EEG signals is of significance for the future implementation of switching driving sound modes fused with EEG signals. Full article

Although declarations of the death of God seem to be provocations announcing the end of the era of theology, this announcement is actually central to the Christian revelation in its most classic forms, as well as to its reworkings in contemporary religious thought. Indeed provocative new possibilities for thinking theologically open up precisely in the wake of the death of God. Already Hegel envisaged a revolutionary new realization of divinity emerging in and with the secular world through its establishment of a total order of immanence. However, in postmodern times this comprehensive order aspired to by modern secularism implodes or cracks open towards the wholly Other. A hitherto repressed demand for the absolute difference of the religious, or for “transcendence”, returns with a vengeance. Th is difference is what could not be stated in terms of the Hegelian System, for reasons that poststructuralist writers particularly have insisted on: all representations of God are indeed dead. Yet this does not mean that they cannot still be powerful, but only that they cannot assign God any stable identity. Nietzsche’s sense of foreboding concerning the death of God is coupled with his intimations of the demise of representation and “grammar” as epistemologically bankrupt, but also with his vision of a positive potential for creating value in the wake of this collapse of all linguistically articulated culture. He points the way towards the emergence of a post-secular religious thinking of what exceeds thought and representation. Full article

The rapid development of nanotechnology has offered the possibility of creating nanosystems that can be used as drug carriers. The use of such carriers offers real opportunities for the development of non-invasive drug delivery through skin structures. However, in addition to the ability to create suitable nanocarriers, it is also necessary to know how they move through dermal layers. The human skin consists of layers with different wettability characteristics, which greatly complicates how introduced substances move through it. In this work, an experimental study of the diffusion process of nanoparticles through partitions with different wettability properties was carried out. Conventional diffusion tests using Franz chambers were used for this purpose. We quantified how the wettability of the barrier, the number of layers, and their mutual configuration affect the transport of nanoparticles. Based on the results, an analysis of the phenomena taking place, depending on the wettability of the partition, was carried out. A model relationship was also proposed to determine the effective diffusion coefficient, taking into account the influence of the wettability and porosity of the barrier. Full article

In the world of finance, considerable attention is given to improving machine learning techniques to predict the future of stock markets. However, for obvious reasons, this turns out to be an unsolvable mission, most likely because the real world is not driven by algorithms but by human beings. In response to this, the present study has its focus on raw affective responses in actual asset managers during their decision making regarding controlled financial scenarios. Nineteen asset managers were invited and asked to make sell/buy decisions related to visual presentations of three different price developments of different assets. The three scenarios were “crash”, “stable” and “gain”. Parallel to their decision making, startle reflex modulation (SRM) was used to measure non-conscious affective responses without demanding any respective explicit responses (no conscious language processing involved). Interestingly, two further factors were introduced. First, all participants had to make their decisions once while being informed that 0% prior investments (low exposure) have been made into the presented assets, and once being informed that a large investment consisting of 25% of ones’ overall portfolio has been made prior to making the decision (high exposure). Second, the factor experience was included dividing all participants into two groups, one with low experience and the other with high experience. First, across both these extra factors, it was found that “crash” scenarios resulted in the most negative affective responses. The most positive affective responses were found for “gain” scenarios, while the “stable” condition was in between. Interestingly, the factor of prior investment (i.e., exposure) had an effect. Non-conscious affective responses during decision making related to the “stable” condition varied as a function of “exposure”. In the low exposure condition, affective responses to decision making during the “stable” scenario were most negative, even more negative than in “crash” scenarios. The factor experience also had an effect, but due to the small sample size, no significant interaction occurred. However, t-tests revealed the same significant effects in the experienced group as found in the 0% prior investment condition. To our knowledge, this is the first empirical investigation measuring non-conscious affective responses during decision making in the context of asset management. Thus, this study might form an interesting basis for new strategies to explore non-conscious human brain functions instead of inventing new algorithms to make asset management more successful. Full article

In this study we propose to use for bioprinting a bioink enriched with a recombinant RE15mR protein with a molecular weight of 26 kDa, containing functional sequences derived from resilin and elastin. The resulting protein also contains RGD sequences in its structure, as well as a metalloproteinase cleavage site, allowing positive interaction with the cells seeded on the construct and remodeling the structure of this protein in situ. The described protein is produced in a prokaryotic expression system using an E. coli bacterial strain and purified by a process using a unique combination of known methods not previously used for recombinant elastin-like proteins. The positive effect of RE15mR on the mechanical, physico-chemical, and biological properties of the print is shown in the attached results. The addition of RE15mR to the bioink resulted in improved mechanical and physicochemical properties and promoted the habitation of the prints by cells of the L-929 line. Full article

A novel DC-assisted fast hot-pressing (FHP) powder sintering technique was utilized to prepare Al/Diamond composites. Three series of orthogonal experiments were designed and conducted to explore the effects of sintering temperature, sintering pressure, and holding time on the thermal conductivity (TC) and sintering mechanism of an Al-50Diamond composite. Improper sintering temperatures dramatically degraded the TC, as relatively low temperatures (≤520 °C) led to the retention of a large number of pores, while higher temperatures (≥600 °C) caused unavoidable debonding cracks. Excessive pressure (≥100 MPa) induced lattice distortion and the accumulation of dislocations, whereas a prolonged holding time (≥20 min) would most likely cause the Al phase to aggregate into clusters due to surface tension. The optimal process parameters for the preparation of Al-50diamond composites by the FHP method were 560 °C-80 MPa-10 min, corresponding to a density and TC of 3.09 g cm⁻³ and 527.8 W m⁻¹ K⁻¹, respectively. Structural defects such as pores, dislocations, debonding cracks, and agglomerations within the composite strongly enhance the interfacial thermal resistance (ITR), thereby deteriorating TC performance. Considering the ITR of the binary solid-phase composite, the Hasselman–Johnson model can more accurately predict the TC of Al-50diamond composites for FHP technology under an optimal process with a 3.4% error rate (509.6 W m⁻¹ K⁻¹ to 527.8 W m⁻¹ K⁻¹). The theoretical thermal conductivity of the binary composites estimated by data modeling (Hasselman–Johnson Model, etc.) matches well with the actual thermal conductivity of the sintered samples using the FHP method. Full article

Sacituzumab govitecan (SG) is a new treatment option for patients with metastatic triple-negative and hormone receptor-positive, HER2-negative breast cancer. This antibody–drug conjugate is currently approved as monotherapy. Palliative radiotherapy is frequently used to treat symptomatic metastases locally. Concurrent use of SG and irradiation was excluded in clinical trials of SG, and there are currently limited published data. We report here a systematic review, as well as a retrospective multi-center study of 17 patients with triple-negative breast cancer who received concurrent SG and radiotherapy. In these patients, concurrent use was found to be efficient, safe and well tolerated. There were no apparent differences in moderate or severe acute toxicity according to the timing of SG administration. Full article

In algebra, the sedenions, an extension of the octonion system, form a 16-dimensional noncommutative and nonassociative algebra over the real numbers. It can be expressed as two octonions, and a function and differential operator can be defined to treat the sedenion, expressed as two octonions, as a variable. By configuring elements using the structure of complex numbers, the characteristics of octonions, the stage before expansion, can be utilized. The basis of a sedenion can be simplified and used for calculations. We propose a corresponding Cauchy–Riemann equation by defining a regular function for two octonions with a complex structure. Based on this, the integration theorem of regular functions with a sedenion of the complex structure is given. The relationship between regular functions and holomorphy is presented, presenting the basis of function theory for a sedenion of the complex structure. Full article

This work aims to expand the structure–property relationships of bromo-containing polyimides and the influence of bromine atoms on the gas separation properties of such materials. A series of intrinsically microporous polyimides were synthesized from 2,2′-dibromo-4,4′,5,5′-bipohenyltetracarboxylic dianhydride (Br-BPDA) and five bulky diamines, (7,7′-(mesitylmethylene)bis(8-methyldibenzo[b,e][1,4]dioxin-2-amine) (MMBMA), 7,7′-(Mesitylmethylene)bis(1,8-dimethyldibenzo[b,e][1,4] dioxin-2-amine) (MMBDA), 4,10-dimethyl-6H,12H-5,11-methanodibenzo[b,f][1,5]diazocine-2,8-diamine (TBDA1), 4,10-dimethyl-6H,12H-5,11-methanodibenzo[b,f][1,5]diazocine-3,9-diamine (TBDA2), and (9R,10R)-9,10-dihydro-9,10-[1,2]benzenoanthracene-2,6-diamine (DAT). The Br-BPDA-derived polyimides exhibited excellent solubility, high thermal stability, and good mechanical properties, with their tensile strength and modulus being 59.2–109.3 MPa and 1.8–2.2 GPa, respectively. The fractional free volumes (FFVs) and surface areas (S_BET) of the Br-BPDA-derived polyimides were in the range of 0.169–0.216 and 211–342 m² g⁻¹, following the order of MMBDA > MMBMA > TBDA2 > DAT > TBDA1, wherein the Br-BPDA-MMBDA exhibited the highest S_BET and FFV and thus highest CO₂ permeability of 724.5 Barrer. Moreover, Br-BPDA-DAT displayed the best gas separation performance, with CO₂, H₂, O₂, N₂, and CH₄ permeabilities of 349.8, 384.4, 69.8, 16.3, and 19.7 Barrer, and H₂/N₂ selectivity of 21.4. This can be ascribed to the ultra-micropores (<0.7 nm) caused by the high rigidity of Br-BPDA-DAT. In addition, all the bromo-containing polymers of intrinsic microporosity membranes exhibited excellent resistance to physical ageing. Full article