Miracle-dz/UniFAR-FTUs huggingface dataset:
Anaerobic Co-Digestion of Sewage Sludge and Trade Wastes: Beneficial and Inhibitory Effects of Individual Constituents

Anaerobic digestion (AD) of sewage sludge can be optimised by adding trade wastes (TWs) because of their nutrient content and boost in biogas formation if non-inhibitory. However, some components in TWs might have an inhibitory impact, such as nitrogen compounds, sulphate, heavy metals, metalloids, halogens and organic pollutants (e.g., phenol). This study aimed to understand the impact of TWs on the co-digestion with sewage sludge to identify appropriate TW loads for sustainable AD operation. The composition of 160 TWs was evaluated and the constituents with potential to cause inhibition or toxicity were tested in bio-methane potential (BMP) tests. The compounds studied in BMP tests included ammonia, zinc, copper, aluminium, mercury, arsenic, chloride, sulphate and nitrate. An improvement was observed at concentrations 2–746 mg Zn/L, 1066–2821 mg Cl/L as zinc sulphate and sodium chloride in biogas production, and 2–746 mg Zn/L, 162 mg SO4/L, 25 mg Hg/L as zinc sulphate, sodium chloride and mercury sulphate in methane production, respectively. Considering the TWs characterised and the results of the BMP tests, a volumetric ratio of 10/90 of TWs and sewage sludge is proposed as a suitable feedstock for co-digestion.
Whole-Genome Analysis Reveals the Dynamic Evolution of Holocentric Chromosomes in Satyrine Butterflies

Butterfly chromosomes are holocentric, i.e., lacking a localized centromere. Potentially, this can lead to rapid karyotypic evolution through chromosome fissions and fusions, since fragmented chromosomes retain kinetic activity, while fused chromosomes are not dicentric. However, the actual mechanisms of butterfly genome evolution are poorly understood. Here, we analyzed chromosome-scale genome assemblies to identify structural rearrangements between karyotypes of satyrine butterfly species. For the species pair Erebia ligea–Maniola jurtina, sharing the ancestral diploid karyotype 2n = 56 + ZW, we demonstrate a high level of chromosomal macrosynteny and nine inversions separating these species. We show that the formation of a karyotype with a low number of chromosomes (2n = 36 + ZW) in Erebia aethiops was based on ten fusions, including one autosome–sex chromosome fusion, resulting in a neo-Z chromosome. We also detected inversions on the Z sex chromosome that were differentially fixed between the species. We conclude that chromosomal evolution is dynamic in the satyrines, even in the lineage that preserves the ancestral chromosome number. We hypothesize that the exceptional role of Z chromosomes in speciation may be further enhanced by inversions and sex chromosome–autosome fusions. We argue that not only fusions/fissions but also inversions are drivers of the holocentromere-mediated mode of chromosomal speciation.
Modeling the Capabilities of High-Performing Project Management Offices in General Contracting Companies

The contemporary literature emphasizes a need to delve into how project management offices (PMOs) can be effectively operated in construction organizations by embedding integrated project management rather than relying on stand-alone project controls. However, capabilities for running high-performing PMOs in this complex industry are still unknown to this growing body of knowledge, which is considered a barrier to the realization of their full potential. To address this gap, the current research explores a factor structure for core capabilities using a cross-validation method with survey data from 395 experts in general contracting organizations. The results revealed that the five-factor measurement model encompasses constructs of competent human resources and supportive culture, strategic alignment, delivery support, knowledge management, and leveraging organizational capabilities. This study extends the current literature by establishing a new measurement model explaining the dimensionality of PMO capabilities.
Reconstructing Floorplans from Point Clouds Using GAN

This paper proposed a method for reconstructing floorplans from indoor point clouds. Unlike existing corner and line primitive detection algorithms, this method uses a generative adversarial network to learn the complex distribution of indoor layout graphics, and repairs incomplete room masks into more regular segmentation areas. Automatic learning of the structure information of layout graphics can reduce the dependence on geometric priors, and replacing complex optimization algorithms with Deep Neural Networks (DNN) can improve the efficiency of data processing. The proposed method can retain more shape information from the original data and improve the accuracy of the overall structure details. On this basis, the method further used an edge optimization algorithm to eliminate pixel-level edge artifacts that neural networks cannot perceive. Finally, combined with the constraint information of the overall layout, the method can generate compact floorplans with rich semantic information. Experimental results indicated that the algorithm has robustness and accuracy in complex 3D indoor datasets; its performance is competitive with those of existing methods.
Survival models for heterogeneous populations derived from stable distributions

SUMMARY A new three-parameter family of distributions on the positive numbers is proposed. It includes the stable distributions on the positive numbers, the gamma, the degenerate and the inverse Gaussian distributions. The family is characterized by the Laplace transform, from which moments, convolutions, infinite divisibility, unimodality and other properties are derived. The density is complicated, but a simple saddlepoint approximation is provided. Weibull and Gompertz distributions are naturally mixed over some of the distributions. The family is natural exponential in one of the parameters. The distributions are relevant for application as frailty distributions in life table methods for heterogeneous populations. Desirable properties of such distributions are discussed. As an example survival after myocardial infarction is considered.
Baroclinic Waves with Parameterized Effects of Moisture Interpreted Using Rossby Wave Components

Abstract A theoretical framework is developed for the evolution of baroclinic waves with latent heat release parameterized in terms of vertical velocity. Both wave–conditional instability of the second kind (CISK) and large-scale rain approaches are included. The new quasigeostrophic framework covers evolution from general initial conditions on zonal flows with vertical shear, planetary vorticity gradient, a lower boundary, and a tropopause. The formulation is given completely in terms of potential vorticity, enabling the partition of perturbations into Rossby wave components, just as for the dry problem. Both modal and nonmodal development can be understood to a good approximation in terms of propagation and interaction between these components alone. The key change with moisture is that growing normal modes are described in terms of four counterpropagating Rossby wave (CRW) components rather than two. Moist CRWs exist above and below the maximum in latent heating, in addition to the upper- and lower-lev.
Analysis of Morphological Parameters and Body Composition in Adolescents with and without Intellectual Disability

Compared to the tremendous volume of studies focusing on children and teenagers without disabilities, research regarding weight and body composition among young populations with an intellectual disability is relatively rare. Their number further decreases when we refer to specific age groups with intellectual deficits, such as children and adolescents younger than 18. In addition, studies are even scarcer when we wish to compare groups of subjects with different degrees of intellectual disability by gender. This study has a constative nature. The research sample comprises 212 subjects—girls and boys with an average age of 17.7 ± 0.2, divided into six groups by gender and type of intellectual disability. The parameters considered within the study include anthropometrical data and body composition determined using a professional device (Tanita MC 580 S). The findings of this study highlight the impact of intellectual disability on body composition in this age category. We hope it will help develop efficient strategies, recommendations, and intervention plans to ensure active participation in physical activities and categorisation within the optimal parameters of body composition indicators.
An alternative to the Inverted Gamma for the variances to modelling outliers and structural breaks in dynamic models

In this paper we propose a new wide class of hypergeometric heavy tailed priors that is given as the convolution of a Student-t density for the location parameter and a Scaled Beta2prior for the squared scale parameter. These priors may have heavier tails than Student-t priors, and the variances have a sensible behaviour both at the origin and at the tail, making it suitable for objective analysis. Since the representa- tion of our proposal is a scale mixture, it is suitable to detect sudden changes in the model. Finally we propose a Gibbs sampler using this new family of priors for modelling outliers and structural breaks in Bayesian dynamic linear models. We demonstrate in a published example, that our proposal is more suitable than the Inverted Gamma's assumption for the variances, which makes very hard to detect structural changes.
Adaptive Fault-Tolerant Control of a Hybrid Canard Rotor/Wing UAV Under Transition Flight Subject to Actuator Faults and Model Uncertainties

This article proposes an adaptive fault-tolerant control scheme for an overactuated hybrid vertical take-off and landing canard rotor/wing unmanned aerial vehicle (UAV) to simultaneously compensate actuator faults and model uncertainties without the requirement of fault information and uncertain bounds. The proposed control scheme is constructed with two separate control modules. The high-level control module is developed with a novel adaptive sliding-mode controller, which is employed to maintain the overall system tracking performance in both faulty and fault-free conditions. The low-level control allocation module is used to distribute the virtual control signals that are generated by the high-level control module among the available redundant actuators. In the case of actuator faults, the proposed adaptive scheme can seamlessly adjust the control parameters to compensate the virtual control error and reconfigure the distribution of control signals among the available redundant actuators. A significant feature of this study is that the stability of the closed-loop system is guaranteed theoretically in the presence of both actuator faults and model uncertainties and overestimation of the adaptive control parameters can be avoided. The effectiveness of the proposed control strategy is validated through comparative simulation tests under different faulty and uncertain scenarios.
Nonparametric Bounds on the Causal Effect of University Studies on Job Opportunities Using Principal Stratification

The authors propose a methodology based on the principal strata approach to causal inference for assessing the relative effectiveness of two degree programs with respect to the employment status of their graduates. An innovative use of nonparametric bounds in the principal strata framework is shown, examining the role of some assumptions in reducing uncertainty about the causal effects and proposing a strategy to use the covariates in the construction of the bounds. In the application, the nonparametric bounds turn out to be quite informative on the average causal effect for the latent group of students who are potentially able to graduate from both degree programs. There is some evidence that the effect is positive for economics with respect to political science, at least for some values of the covariates.
Cisplatin-Loaded Thermosensitive Liposomes Functionalized with Hyaluronic Acid: Cytotoxicity and In Vivo Acute Toxicity Evaluation

Cisplatin (CDDP) is a potent antitumor drug used in first-line chemotherapy against several solid tumors, including breast cancer. However, toxicities and drug resistance limit its clinical application. Thermosensitive liposome (TSL) functionalized with hyaluronic acid (HA) containing cisplatin (TSL-CDDP-HA) was developed by our research group aiming to promote the release of CDDP in the tumor region under hyperthermia conditions, as well as to decrease toxicity. Thus, this study aimed to evaluate this new formulation (HA-coated TSL-CDDP) concerning in vitro behavior and in vivo toxicity compared to non-coated TSL-CDDP and free CDDP. Cytotoxicity assays and nuclear morphology were carried out against triple-negative breast cancer cells (MDA-MB-231), while an in vivo toxicity study was performed using healthy Swiss mice. The results showed an increase (around 3-fold) in cytotoxicity of the cationic formulation (non-coated TSL-CDDP) compared to free CDDP. On the other hand, TSL-CDDP treatment induced the appearance of 2.5-fold more senescent cells with alteration of nuclear morphology than the free drug after hyperthermia condition. Furthermore, the association of liposomal formulations treatment with hyperthermia increased the percentage of apoptotic cells compared to those without heating. The percentage of apoptotic cells was 1.7-fold higher for TSL-CDDP-HA than for TSL-CDDP. For the in vivo toxicity data, the TSL-CDDP treatment was also toxic to healthy cells, inducing nephrotoxicity with a significant increase in urea levels compared to the saline control group (73.1 ± 2.4 vs. 49.2 ± 2.8 mg/mL). On the other hand, the HA-coated TSL-CDDP eliminated the damages related to the use of CDDP since the animals did not show changes in hematological and biochemical examinations and histological analyses. Thus, data suggest that this new formulation is a potential candidate for the intravenous therapy of solid tumors.
What is physics?

‘Physics deals with those phenomena of the inanimate world which do not produce deep changes in the structure of matter’ the old schoolbooks said. In modern terms this would mean that classical physics restricted itself to phenomena t room temperature which modified only the secondary intermolecular bonds in condensed matter, i.e. the energy concentration is supposed to be smaller than 1 eV per atom. ‘Chemistry deals with those phenomena of the inanimate world which imply essential change in the structure of matter’. The Bunsen flame is the symbol of chemistry. Chemists play with fire: they concentrate several electron volts on a molecule because they intend to rearrange its covalent bonds. ‘Astronomy works with celestial objects’. Note the difference between observation nd experiment, between observatory and laboratory. ‘Biology investigates living entities’. The saturating valence appeared to be qualitatively different from the force of a spring. In the last century no one asked what was a part of physics, what of chemistry. Pasteur proved that a living being can descend only from other living ones. The elusive vis vitalis made a sharp distinction between lifeless and living. But we now understand that these boundaries were never impenetrable, rather they were unexplored frontiers separating the territories of science. The revolutionary 20th century had no respect for traditions either in society or in science. The pioneers of modern physics entered the terra incognita without inhibitions. They solved the puzzle of the H2 molecule, explored the centre of the sun, redesigned the atomic nucleus and now they are busy mapping the depths of the proton. They created tools to explore the alpha helix of protein and the double helix of genetic material. The wide strips of the terra incognita shrank to small white spots between the different branches of science. The real challenge for the coming generation is a great universal unknown surrounding our knowledge, stretching towards the infinitely small, infinitely large and infinitely complex .
Learning Car-Following Behaviors for a Connected Automated Vehicle System: An Improved Sequence-to-Sequence Deep Learning Model

Data-driven car-following modeling is of great significance to traffic behavior analysis and the development of connected automated vehicle (CAV) technology. The existing researches focus on reproducing the car-following process by capturing the behavior of the host vehicle using the information of its nearest preceding vehicle. While the other preceding vehicles may affect the host vehicle as well. To fill the gap above, this paper presents an improved sequence-to-sequence deep learning-based (ISDL) car-following model for a CAV system. Firstly, the kinematics information considering the multiple preceding vehicles are organized as the input characteristics. Secondly, an improved sequence-to-sequence deep learning framework is proposed by integrating an encoder with the bidirectional gated recurrent unit (GRU) neural network and a decoder using an attention-based GRU neural network in an end-to-end fashion. Finally, the car-following data with multiple preceding vehicles captured from the NGSIM dataset are employed to train and calibrate the proposed model. Experimental results indicate that the deep learning-based models’ performance in learning heterogeneous driving behavior can be enhanced by adding information about multiple preceding vehicles. In addition, the proposed ISDL model outperforms the benchmark car-following models in terms of the accuracy of the simulated speeds and simulated positions. Through tests on platoon simulation, the ISDL model is capable of reshaping the traffic oscillation phenomenon as well.
Development of X-ray triscopic imaging system towards three-dimensional measurements of dynamical samples

X-ray triscopic imaging system was developed to observe dynamics of samples from three different directions simultaneously. A part of the monochromatic X-ray beam was reflected under Bragg condition using a Si(111) crystal to produce an X-ray beam in a direction different from the incident beam. In the triscopic imaging system, silicon crystals were set at both sides of the wide incident X-ray beam to produce three beams. To obtain a large field of view in the reflected beam, a lapped silicon crystal was used instead of a conventional crystal with a mirror surface. The maximum field of view of 20 mm × 20 mm was achieved with the X-ray energy of 20 keV. X-ray triscopic images could be obtained simultaneously by placing an X-ray detector with a large field of view near the sample. X-ray triscopic images with refraction contrast could be obtained by placing three X-ray detectors, which were synchronized by external trigger signals, at far position from the sample. A live mouse was studied as a dynamical sample. Motions of the heart and lungs in the mouse were clearly observed from three different directions with refraction contrast.
Smart Chondroitin Sulfate Micelles for Effective Targeted Delivery of Doxorubicin Against Breast Cancer Metastasis

Introduction Metastasis is a major challenge in breast cancer therapy. The successful chemotherapy of breast cancer largely depends on the ability to block the metastatic process. Herein, we designed a dual-targeting and stimuli-responsive drug delivery system for targeted drug delivery against breast cancer metastasis. Methods AS1411 aptamer-modified chondroitin sulfate A-ss-deoxycholic acid (ACSSD) was synthesized, and the unmodified CSSD was used as the control. Chemotherapeutic drug doxorubicin (DOX)-containing ACSSD (D-ACSSD) micelles were prepared by a dialysis method. The ACSSD conjugate was confirmed by Fourier transform infrared spectroscopy (FTIR), nuclear magnetic resonance (NMR), dynamic light scattering (DLS), and transmission electron microscopy (TEM). In vitro cellular uptake and cytotoxicity of D-ACSSD micelles were studied by confocal laser scanning microscopy (CLSM) and MTT assay in breast tumor cells. The inhibition capability of D-ACSSD micelles in cell migration and invasion was carried out in 4T1 cells. In vivo antitumor activity of DOX-containing micelles was investigated in metastatic 4T1-bearing Balb/c mice. Results D-ACSSD and DOX-loaded CSSD (D-CSSD) micelles exhibited high drug encapsulation content and reduction-responsive characteristics. D-ACSSD micelles were spherical in shape. Compared with D-CSSD, D-ACSSD showed higher cellular uptake and more potent killing activity in 4T1 and MDA-MB-231 cells. Additionally, D-ACSSD exhibited stronger inhibitory effects on the invasion and migration of highly metastatic 4T1 cells than unmodified D-CSSD. Among the DOX-containing formulations, D-ACSSD micelles presented the most effective inhibition of tumor growth and lung metastasis in orthotopic 4T1-bearing mice in vivo. It also revealed that ACSSD micelles did not exhibit obvious systemic toxicity. Conclusion The smart D-ACSSD micelles could be a promising delivery system for the therapy of metastatic breast cancer.
Gas Sensing of Laser-Produced Hybrid TiO2-ZnO Nanomaterials under Room-Temperature Conditions

The preparation method can considerably affect the structural, morphological, and gas-sensing properties of mixed-oxide materials which often demonstrate superior photocatalytic and sensing performance in comparison with single-metal oxides. In this work, hybrids of semiconductor nanomaterials based on TiO2 and ZnO were prepared by laser ablation of Zn and Ti plates in water and then tested as chemiresistive gas sensors towards volatile organics (2-propanol, acetaldehyde, ethanol, methanol) and ammonia. An infrared millisecond pulsed laser with energy 2.0 J/pulse and a repetition rate of 5 Hz was applied to Zn and Ti metal targets in different ablation sequences to produce two nano-hybrids (TiO2/ZnO and ZnO/TiO2). The surface chemistry, morphology, crystallinity, and phase composition of the prepared hybrids were found to tune their gas-sensing properties. Among all tested gases, sample TiO2/ZnO showed selectivity to ethanol, while sample ZnO/TiO2 sensed 2-propanol at room temperature, both with a detection limit of ~50 ppm. The response and recovery times were found to be 24 and 607 s for the TiO2/ZnO sensor, and 54 and 50 s for its ZnO/TiO2 counterpart, respectively, towards 100 ppm of the target gas at room temperature.
Eco-Innovation Performance of Lithuania in the Context of European Environmental Policy: Eco-Innovation Indicators and Efficiency

The European Union (EU) has made eco-innovation and green technology a priority as they are essential to the continent’s long-term prosperity. To move towards sustainable economic growth, eco-innovation takes a significant role in the transition process. The aim of the article is to use the eco-innovation indicators as an instrument to measure the eco-innovation performance of Lithuania in the context of the EU Green Deal in order to analyze and assess the components and indicators of the eco-innovation index for Lithuania. Following the aim of the article, a set of research hypotheses will be formulated. The evaluation of eco-innovation indicators in Lithuania relative to EU countries using Eco-IS indicators, determination of eco-innovation efficiency using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method, and identification of necessary eco-innovation policies for sustainable growth are the objectives of this paper. The research results present the positive impact of eco-innovation activities in the EU on Lithuania, and vice versa. Lithuania was affected positively by eco-innovation activities of other EU nations. The outcome of the study indicates its relevance by highlighting Lithuania’s position among the lowest countries in terms of eco-innovation adoption, hence new research pathways for the creation and implementation of policies to solve the current situation are provided.