Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancing Oral Bioavailability and Brain Biodistribution of Perillyl Alcohol Using Nanostructured Lipid Carriers

Perillyl alcohol (POH), a bioactive monoterpenoid derived from limonene, shows promise as an antitumor agent for brain tumor treatment. However, its limited oral bioavailability and inadequate brain distribution hinder its efficacy. To address these challenges, this study developed nanostructured lipid carriers (NLCs) loaded with POH to improve its brain biodistribution. The NLCs prepared using hot homogenization exhibited an average diameter of 287 nm and a spherical morphology with a polydispersity index of 0.143. High encapsulation efficiency of 99.68% was achieved. X-ray diffraction analyses confirmed the semicrystalline state of POH-loaded NLCs. In vitro release studies demonstrated a biphasic release profile. Stability studies in simulated gastric and intestinal fluids confirmed their ability to withstand pH variations and digestive enzymes. In vivo pharmacokinetic studies in rats revealed significantly enhanced oral bioavailability of POH when encapsulated in the NLCs. Biodistribution studies showed increased POH concentration in brain tissue with NLCs compared with free POH, which was distributed more in non-target tissues such as the liver, lungs, kidneys, and spleen. These findings underscore the potential of NLCs as effective delivery systems for enhancing oral bioavailability and brain biodistribution of POH, providing a potential therapeutic strategy for brain tumor treatment.
Uncountably many maximizing measures for a dense subset of continuous functions

Ergodic optimization aims to single out dynamically invariant Borel probability measures which maximize the integral of a given ‘performance’ function. For a continuous self-map of a compact metric space and a dense set of continuous functions, we show the existence of uncountably many ergodic maximizing measures. We also show that, for a topologically mixing subshift of finite type and a dense set of continuous functions there exist uncountably many ergodic maximizing measures with full support and positive entropy.
Fault-Tolerant Practical Prescribed-Time Formation-Containment Control of Multi-Agent Systems on Directed Graphs

This work solves the analysis and protocol design problems of the prescribed-time formation-containment (FC) control of double-integrator multi-agent systems (MASs) on directed graphs in the presence of unknown and time-varying actuator faults. First, a novel kind of distributed prescribed-time observers (DPTOs) is designed for the leaders and the followers, respectively, which could achieve distributed zero-error estimation on directed graphs within a predefined time interval. Based on this DPTO, a decentralized protocol equipped with a time-scaling function is proposed, which possesses both prescribed-time performance and fault-tolerant merits against both additive and multiplicative faults. This protocol ensures that the MAS achieves fault-tolerant FC in a cooperatively ultimately uniformly bounded sense after a prescribed time interval, while the formation error and containment error further converge to zero at an exponentially predefined speed. Also, the upper bounds of the tracking error, formation error, and containment error have been given explicitly. The effectiveness of the proposed DPTO-based protocol is proven via an illustrative simulation example.
Event‐triggered neural control for non‐strict‐feedback systems with actuator failures

This study is concerned with an adaptive event-triggered control problem for non-linear non-strict-feedback systems subject to actuator failures. For actuator failures, both total loss of effectiveness (TLOE) and partial loss of effectiveness (PLOE) are considered. The event-triggered mechanism is proposed in this study, which may influence measurement errors. Neural networks (NNs) are used to approximate unknown non-linear functions, and a neural observer is designed to estimate unknown state variables. Then a neural tracking controller is constructed to reduce the communication burden via backstepping technique. The new controller ensures that the output of the system reaches to the same trajectory with the reference signal, and it also guarantees the boundedness of all the closed-loop signals. Finally, a simulation example is used to testify the results.
Analysis of the Application of Material Requirement Planning Method in Nature to Achieve the Production Targets of the Moraja Donggala Social Forestry Business Group

This study aims to analyze the Application of Material Requirement Planning (MRP) in achieving production targets in the Moraja Social Forestry Business Group (KUPS). The type of research used is a descriptive qualitative method using Material Requirement Planning (MRP) analysis. The results showed that KUPS Moraja has not been able to fully implement MRP, which is in the form of a Master Production Schedule and is on a manufacturing or manufacturing scale. Then related to planning, scheduling orders and controlling raw material inventory items have been carried out even with a conventional system where the Master Production Schedule (MPS) KUPS Moraja carries out or schedules production once a month in week 2 (two) or if there are orders from customers so that in a year the production order schedule occurs 12 (twelve) times. Kups Moraja on Bill of Material (BOM) consists of three processes, namely the drying, grinding, and packing processes. Furthermore, the Inventory Record (Inventory Record), it can be known that the raw materials used during the 2021 period were 39 kg 06 ounces of Moringa leaves. Then for the lead time, the entire production process takes 7 (seven) days, which consists of stages, namely the drying process of Moringa tea takes 5 days, while the grinding process of Moringa tea takes 1 day and the packaging process takes 1 day. Overall, the supply of Moringa raw materials has been controlled using conventional techniques.
Identification and validation of a novel overall survival prediction model for immune-related genes in bone metastases of prostate cancer

Immunotherapy has become a revolutionary treatment for cancer and brought new vitality to tumor immunity. Bone metastases are the most prevalent metastatic site for advanced prostate cancer (PCa). Therefore, finding new immunotherapy targets in PCa patients with bone metastasis is urgently needed. We conducted an elaborative bioinformatics study of immune-related genes (IRGs) and tumor-infiltrating immune cells (TIICs) in PCa bone metastases. Databases were integrated to obtain RNA-sequencing data and clinical prognostic information. Univariate and multivariate Cox regression analyses were conducted to construct an overall survival (OS) prediction model. GSE32269 was analyzed to acquire differentially expressed IRGs. The OS prediction model was established by employing six IRGs (MAVS, HSP90AA1, FCGR3A, CTSB, FCER1G, and CD4). The CIBERSORT algorithm was adopted to assess the proportion of TIICs in each group. Furthermore, Transwell, MTT, and wound healing assays were employed to determine the effect of MAVS on PCa cells. High-risk patients had worse OS compared to the low-risk patients in the training and validation cohorts. Meanwhile, clinically practical nomograms were generated using these identified IRGs to predict the 3- and 5-year survival rates of patients. The infiltration percentages of some TIICs were closely linked to the risk score of the OS prediction model. Some tumor-infiltrating immune cells were related to the OS. FCGR3A was closely correlated with some TIICs. In vitro experiments verified that up-regulation of MAVS suppressed the proliferation and metastatic abilities of PCa cells. Our work presented a thorough interpretation of TIICs and IRGs for illustrating and discovering new potential immune checkpoints in bone metastases of PCa.
Enzymatic properties of alcohol dehydrogenase PedE_M.s. derived from Methylopila sp. M107 and its broad metal selectivity

As an important metabolic enzyme in methylotrophs, pyrroloquinoline quinone (PQQ)-dependent alcohol dehydrogenases play significant roles in the global carbon and nitrogen cycles. In this article, a calcium (Ca2+)-dependent alcohol dehydrogenase PedE_M. s. , derived from the methylotroph Methylopila sp. M107 was inserted into the modified vector pCM80 and heterologously expressed in the host Methylorubrum extorquens AM1. Based on sequence analysis, PedE_M. s. , a PQQ-dependent dehydrogenase belonging to a methanol/ethanol family, was successfully extracted and purified. Showing by biochemical results, its enzymatic activity was detected as 0.72 U/mg while the Km value was 0.028 mM while employing ethanol as optimal substrate. The activity of PedE_M. s. could be enhanced by the presence of potassium (K+) and calcium (Ca2+), while acetonitrile and certain common detergents have been found to decrease the activity of PedE_M. s. In addition, its optimum temperature and pH were 30°C and pH 9.0, respectively. Chiefly, as a type of Ca2+-dependent alcohol dehydrogenase, PedE_M. s. maintained 60–80% activity in the presence of 10 mM lanthanides and displayed high affinity for ethanol compared to other PedE-type enzymes. The 3D structure of PedE_M. s. was predicted by AlphaFold, and it had an 8-bladed propeller-like super-barrel. Meanwhile, we could speculate that PedE_M. s. contained the conserved residues Glu213, Asn300, and Asp350 through multiple sequence alignment by Clustal and ESpript. The analysis of enzymatic properties of PedE_M. s. enriches our knowledge of the methanol/ethanol family PQQ-dependent dehydrogenase. This study provides new ideas to broaden the application of alcohol dehydrogenase in alcohol concentration calculation, biosensor preparation, and other industries.
Label-efficient deep semantic segmentation of intracranial hemorrhages in CT-scans

Intracranial hemorrhage (ICH) is a common finding in traumatic brain injury (TBI) and computed tomography (CT) is considered the gold standard for diagnosis. Automated detection of ICH provides clinical value in diagnostics and in the ability to feed robust quantification measures into future prediction models. Several studies have explored ICH detection and segmentation but the research process is somewhat hindered due to a lack of open large and labeled datasets, making validation and comparison almost impossible. The complexity of the task is further challenged by the heterogeneity of ICH patterns, requiring a large number of labeled data to train robust and reliable models. Consequently, due to the labeling cost, there is a need for label-efficient algorithms that can exploit easily available unlabeled or weakly-labeled data. Our aims for this study were to evaluate whether transfer learning can improve ICH segmentation performance and to compare a variety of transfer learning approaches that harness unlabeled and weakly-labeled data. Three self-supervised and three weakly-supervised transfer learning approaches were explored. To be used in our comparisons, we also manually labeled a dataset of 51 CT scans. We demonstrate that transfer learning improves ICH segmentation performance on both datasets. Unlike most studies on ICH segmentation our work relies exclusively on publicly available datasets, allowing for easy comparison of performances in future studies. To further promote comparison between studies, we also present a new public dataset of ICH-labeled CT scans, Seq-CQ500.
Towards a Guideline for UAV-Based Data Acquisition for Geomorphic Applications

Recent years have seen a rapid rise in the generation of high-resolution topographic data using custom-built or commercial-grade Unmanned Aerial Vehicles (UAVs). Though several studies have demonstrated the application potential of UAV data, significant knowledge gaps still exist in terms of proper documentation of protocols for data acquisition, post-flight data processing, error assessments, and their mitigation. This work documents and provides guidelines for UAV data acquisition and processing from several years of field experience in diverse geomorphic settings across India, including undulating topography (~17 km2), alluvial plains (~142 km2), lowland-river basin (~66 km2), and a highly urbanized area (~5 km2). A total of 37,065 images with 16 and 20 Megapixels and 604 ground control points (GCPs) were captured with multiple UAV systems and processed to generate point clouds for a total area of ~230 km2. The Root Mean Square Error (RMSE) for each GCP for all sites ranged from 6.41 cm to 36.54 cm. This manuscript documents a comprehensive guideline for (a) pre-field flight planning and data acquisition, (b) generation and removal of noise and errors of the point cloud, and (c) generation of orthoimages and digital elevation models. We demonstrate that a well-distributed and not necessarily uniformly distributed GCP placement can significantly reduce doming error and other artifacts. We emphasize the need for using separate camera calibration parameters for each flight and demonstrate that errors in camera calibration can significantly impact the accuracy of the point cloud. Accordingly, we have evaluated the stability of lens calibration parameters between consumer-grade and professional cameras and have suggested measures for noise removal in the point cloud data. We have also identified and analyzed various errors during point cloud processing. These include systematic doming errors, errors during orthoimage and DEM generation, and errors related to water bodies. Mitigation strategies for various errors have also been discussed. Finally, we have assessed the accuracy of our point cloud data for different geomorphic settings. We concluded that the accuracy is influenced by Ground Sampling Distance (GSD), topographic features, and the placement, density, and distribution of GCPs. This guideline presented in this paper can be extremely beneficial to both experienced long-term users and newcomers for planning the UAV-based topographic survey and processing the data acquired.
Prediction of microwave absorption properties of tetrapod-needle zinc oxide whisker radar absorbing material without prior knowledge

The radar absorbing material (RAM) containing a tetrapod-needle zinc oxide whisker (T-ZnOw) has been proved to have good efficiency of microwave absorption. However, the available theoretical models, which are intended to predict the microwave absorbing properties of such an interesting composite, still cannot work well without some prior knowledge, like the measured effective electromagnetic parameters of the prepared T-ZnOw composite. Hence, we propose a novel predictive method here to calculate the reflectivity of T-ZnOw RAM without prior knowledge. In this method, the absorbing ability of this kind of material is divided into three main aspects: the unstructured background, the conductive network, and the nanostructured particle. Then, the attenuation properties of these three parts are represented, respectively, by three different approaches: the equivalent spherical particle and the static strong fluctuation theory, the equivalent circuit model obtained from the complex impedance spectra technology, and the combination of four different microscopic electromagnetic responses. The operational calculation scheme can be obtained by integrating these three absorption effects into the existing theoretical attenuation model. The reasonable agreement between the theoretical and experimental data of a T-ZnON/SiO2 composite in the range of 8–14 GHz shows that the proposed scheme can predict the microwave absorption properties of the T-ZnOw RAM. Furthermore, a detailed analysis of these three mechanisms indicates that, on the one hand, the background plays a dominant role in determining the real part of the effective permittivity of the T-ZnOw composite while the network and the particle are the decisive factors of its material loss; on the other hand, an zero-phase impedance, i.e., a pure resistance, with appropriate resonance characteristic might be a rational physical description of the attenuation property of the conductive network, but it is difficult to realize such an impedance property by the traditional resistance and capacitance network. As a result, a series resonant circuit with a relatively low quality factor is introduced to approximate the material loss caused by the network. Finally, the different combinations of these three absorbing mechanisms are analyzed to further display their roles in the overall absorbing performance.
Exergame for post-stroke rehabilitation among elderly patients: A systematic review and meta-analysis

Advancement in gaming technology, including exergame, is thought to offer a promising innovation in rehabilitative treatment owing to its interactive and joyful natures. Elderly, in addition to being prevalent in stroke, they have different perspectives and adaptability toward the utilization of exergame in post-stroke rehabilitation. The aim of this study was to evaluate the effectiveness of exergame-based rehabilitation in ameliorating stroke-associated cognitive impairment among elderly patients. This systematic review followed the Preferred Reporting Item for Systematic Review and Meta-Analysis (PRISMA) guideline. The literatures were retrieved from the searches on PubMed, Scopus, and Embase databases using a combination of ‘exergame’, ‘stroke’, and ‘elderly’ along with their respective synonyms. Included studies were controlled observational studies and randomized clinical trials with subjects’ mean age >60 years old, measuring global cognitive and/or five cognitive domains (attention, language, executive function, memory, and visuospatial ability). Quality appraisals were performed based on the Cochrane ‘risk-of-bias tool’ and Physiotherapy Evidence Database Scale. Studies with high and good qualities were included in the meta-analyses. Six randomized controlled trials involving 179 patients were included in meta-analysis. Studies had variations in terms of type (combination of exergame-based and conventional rehabilitation or exergame-based only) and duration of interventions (30–110 min), length of observation (2–6 weeks), and tools used to examine cognitive outcomes. As compared with conventional rehabilitation, exergame-based rehabilitation was significantly more effective to improve global cognitive based on Montreal Cognitive Assessment Score in acute stroke patients (n=4; mean difference (MD) 3.66; 95% confidence interval (95%CI): 2.08, 5.24; p<0.00001), but significantly less effective in chronic stroke patients (n=2; MD -1.54; 95%CI: -2.28, -0.81; p<0.0001). In conclusion, global cognitive of elderly patients with acute strokes could be improved through exergame-based rehabilitation which is more effective as compared with conventional therapy.
Multibeam interferometric optical tweezers

Abstract. Using the interference of N collimated laser beams, optical lattices with N-fold rotational symmetry are generated over the interface of two semi-infinite dielectric media. The interaction of small dielectric particles with these interference patterns is investigated using Rayleigh approximation. The polarization state of the interfering beams considerably influences the interference patterns and potential landscapes. Therefore, both parallel and perpendicular polarized interfering beams are considered and the corresponding potential profiles are compared and analyzed. We also study how the number of interfering waves, incident and azimuth angles, and initial phases of the incident beams influence optical lattices and potential profiles. It is found that the ring-shaped patterns with good confinement properties can be achieved by increasing the number of incident beams. In addition, by increasing the number of incident beams one can make an optical trap with sharper intensity gradient and deeper potential well, which is an advantage for trapping small Rayleigh particles. The lattices resulting from the interference of N incident waves with different incident angles are also investigated. Furthermore, the effects of changing the azimuth angles between two adjacent incident wave vectors on the intensity patterns are studied. The proposed configuration and the numerical results can find numerous applications in particle arrangement, particle sorting, and the creation of quasicrystals. We believe that interference approaches have many potential capabilities for molding light wavefronts and creating multiple traps with sophisticated patterns.
Numerical Simulation of the Collision Breakage Process between the Agglomerate and Hammer in a Hammer Crusher Using DEM

This paper focuses on simulating the collision breakage process between the agglomerate and hammer in a hammer crusher by the discrete element method (DEM) as the interaction between particles. This enables us to consider the energy change in the collision breakage process of the hammer. The agglomerate model is built by using the EDEM 2.7 software according to the principle of closest packing in crystallography, while the hammer model is modeled into an assembly of different sizes of spherical particles to make the collision breakage process between the agglomerate and hammer as the one of interrelation of particles. With these models, we mainly investigated collision force, collision impulse, energy breaking agglomerate, and the relationship between the specific breakage energy and agglomerate damage ratio. The collision force is represented as Gaussian function, the collision impulse is represented by the function of the mass ratio of agglomerate to hammer and the product of agglomerate mass and collision velocity, and the relationship between the specific breakage energy and agglomerate damage ratio is represented by exponential function. Finally, it can be seen from this study that, when crushing the agglomerate by hammer impact, it is necessary to increase the specific breakage energy by 1.75 times in order to increase the agglomerate damage ratio from 85% to 90% but 2.13 times in order to increase 95%. The proposed method can be used for the further development and design of the various types of crusher.
HIGH RESOLUTION SPECTRA OF GALAXIES Models and inversions

We present inversion techniques which aim at recovering the composite nature and the kinematics of a stellar population from its high resolution absorption line spectrum. The originality of the combined inversion is its potential to recover both the stellar content and the kinematics sim- ultaneously. These techniques use new synthetic high resolution spectra produced by PEGASE and minimization algorithms. We apply them to mock data representing the bulge and disk population of the inner region of spiral galaxies. The high resolution spectrographs now installed on 10m-class telescopes open new perspectives in the exploration of the formation of galaxies. Absorption line spectra with a good spatial sampling will provide new information on the nature of the stellar components of a galaxy, as well as on their kinematics. This poster presents the first attempt to fit simultaneously the local line-of-sight velocity distribution (LOSVD) and the nature of the stellar population. It is based on efficient non- parametric inversion procedures.