Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of several macroalgae species on methane emission and antioxidant activity based on in vitro rumen fermentation characteristics

Marine macroalgae are the prospective and promising Indonesian natural resources containing bioactive compounds. This study aimed at evaluating various seaweed species with optimal biological activity to mitigate in vitro rumen methane emission and to confirm their antioxidant properties. In addition, relationships among several phenolic fractions and methane (CH4) production of seaweeds were elucidated by Pearson Correlation to screen seaweeds for their capacity to reduce CH4 formation. For in vitro batch cultures experiment, the diets were 500 mg of a substrate of seaweed. They were incubated with 50 ml of buffered rumen fluid (1:2 ratio of rumen fluid to buffer media) in a 100 ml serum vial at 39°C for 72 hours incubation time. A randomized block design was carried out with 14 dried seaweed treatments and 5 different cattle rumen fluid groups as a block. For total phenol, flavonoid, and antioxidant activity, a completely randomized design with 14 treatments and 3 replications was carried out. Data were analyzed by Analysis of Variance (ANOVA) and Duncan analysis. The results showed that the lowest methane production (ml/g DM incubated) significantly (P<0.05) was reduced by Halymenia sp. (0.24) and Caulerpa racemosa (0.41). Caulerpa racemosa showed high flavonoid content (1.5 mg Quercetin/g) and Ulva lactuca had the highest phenol content (0.55 mg Gallic Acid/g). Gracilaria coronopifolia had strong antioxidant activity DPPH radical scavenging activity (77.5% inhibition). It was concluded that Halymenia sp. , Caulerpa racemosa and Gracilaria coronopifolia could be used as methane inhibitors and antioxidants for ruminants.
Biogenic Emissions and Nocturnal Ozone Depletion Events at the Amphitrite Point Observatory on Vancouver Island

ABSTRACT Routine monitoring stations on the west coast of North America serve to monitor baseline levels of criteria pollutants such as ozone (O3) arriving from the Pacific Ocean. In Canada, the Amphitrite Point Observatory (APO) on Vancouver Island has been added to this network to provide regional baseline measurements. In 2014, McKendry, I. G. , Christensen, E. , Schiller, C. , Vingarzan, R. , Macdonald, A. M. , & Li, Y. (2014) reported frequent nocturnal O3 depletion events (ODEs) at APO that generally correlated with alongshore winds, elevated concentrations of carbon dioxide (CO2), and stable boundary layer conditions but the cause (causes) for this remains (remain) unclear. This manuscript presents results from the Ozone-depleting Reactions in a Coastal Atmosphere (ORCA) campaign, which took place in July 2015 to further investigate ODEs at APO. In addition to the long-term measurements at the site (e.g., CO2 and O3 mixing ratios), abundances of biogenic volatile organic compounds (BVOC) and aerosol size distributions were quantified. On the majority of measurement nights, ODEs were observed and characterized by a simultaneous increase in CO2 and BVOC abundances, in particular of limonene, a terpene 2.5 times more reactive with respect to oxidation by O3 than other monoterpenes. Back trajectory calculations showed that ODEs occurred mainly in air masses originating from the west-northwest where the air would have travelled parallel to the coastline and above kelp forests. Head-space analyses of seaweed samples showed that bull kelp is a source of gas-phase limonene, consistent with its high relative abundance in air masses from the west-northwest sector. However, the enhanced terpene and CO2 content showed that the air likely also came in contact with terrestrial vegetation via mesoscale transport phenomena (such as slope flows and land–sea breeze circulations) that were generally poorly captured by the back trajectories. The absence of aerosol growth during ODEs indicates that dry deposition is likely the primary O3 loss mechanism.
Compression and Reconstruction of Magnetotelluric Data Based on Convolutional Neural Network

Magnetotelluric method is one of the important geophysical methods, and its signal acquisition requires more stacking times and longer stacking time. With the development of instruments, the acquisition time becomes longer and the amount of data becomes larger, which brings new challenges to data storage and transmission. Aiming at the above problems, a compression and reconstruction technology of magnetotelluric time series based on convolutional neural network is proposed. This paper introduces two convolutional autoencoders based on convolutional neural networks, which can effectively compress data space, improve transmission efficiency, and have high data reconstruction accuracy. Using the measured magnetotelluric time series, two autoencoder models based on convolutional networks are verified in this paper, which proves the feasibility of convolutional autoencoders in magnetotelluric data compression; the results show that model 2 can better reproduce It constructs the magnetotelluric time series, and has high training efficiency and good generalization ability.
Assessment of the energy consumption of indoor farming for different climates and lighting system intensity

Nowadays, due to the energy, water, and arable land crises, as well as the constant global population growth and urbanization, water, energy, and food sources are strongly linked to each other, and a comprehensive analysis including all the influencing factors has to be carried out. In this context, the need to improve the energy performance of traditional cultivation systems, as well as to develop alternative and innovative ones, is causing a shift in interest from greenhouses to indoor farming methods (such as vertical farms) in the agricultural sector. In fact, they allow for completely controlled crop production without the use of chemical pesticides. Moreover, their productivity is independent of external conditions and improved compared to traditional systems. However, their energy consumption is larger than that of greenhouses. To evaluate the techno-economic feasibility of such systems, a comprehensive model of a vertical farm, including air conditioning, lighting systems, and plant evapotranspiration, has been developed to quantify the energy share for the different elements of the system (air conditioning and lighting) and to relate the energy consumption to the kilogram of produced crop, analysing exclusively the growth phase. The analysis is carried out for different cities and considers different scenarios in terms of lighting and electricity costs.
A Simple Model Generator for Radar Sounding Applications Based on Stochastic Media Model and gprMax

Ground penetrating radar (GPR), or more generically called radar sounding, is an established technique for probing subsurface objects and sublayer structures. Simulating pre-constructed models and comparing with the real-world observations can contribute to retrieve the geometrical and physical properties of subsurface objects. However, most GPR simulations are limited to geometrically simple models with homogeneous physical properties of subsurface media which are generally unable to represent the real-world situations. In this paper, we develop a simple model generator by combining the stochastic media model and gprMax, an open-source software for electromagnetic simulations, to jointly generate models with geometrically random fragments, which are forward models with minimum human intervention. These easily prepared and simulated models can enrich the model training datasets which can be further utilized in machine learning for GPR retrieval algorithms.
Design of H5 Transformerless Inverter for Photovoltaic System

There are two distinct categories of sources for generating electrical power: conventional and non-conventional. At now, traditional sources such as coal, gas, and nuclear power are widely employed for the purpose of electricity generation; nevertheless, they are associated with detrimental environmental consequences. Therefore, it is crucial to utilize renewable energy sources like sun and wind to provide some of the necessary electrical power. The driving force behind this transition is the imperative for clean energy, the mitigation of greenhouse gas emissions, and the capacity to create electricity in geographically isolated regions. A proposed solution for using solar energy in single-phase AC applications involves the implementation of an H5 converter topology. The proposed architecture employs twin input DC-DC boost converters, which incorporate solar panels and batteries, to manage the desired output DC voltage. The H5 topology has notable suitability for single-phase transformerless inverters in AC applications encompassing low and high-power demands, owing to its capacity to effectively mitigate leakage current. In order to evaluate the viability of the suggested methodology, a MATLAB simulation is performed to simulate the complete procedure. Furthermore, the development of a prototype is underway in order to assess and verify the performance and outcomes of the converter. The simulation will be conducted with either the MATLAB.
Calculation of Noise Cross-Correlation Functions Between Different Types of Sensors without Removing Instrument Responses

The noise cross-correlation function between two stations provides an efficient way for understanding the subsurface structure. Removing instrument response is a necessary step for the calculation of the noise cross-correlation function (NCF) between different types of sensors, which requires the knowledge of the instrument response. However, the instrument response files may be missing or not provided, restricting us to only the calculation of NCF between the same type of instruments. We propose to calculate the NCF between different sensors deployed at the same site and obtain the phase differences between different instrument responses. The phase differences can then be removed resulting in the unbiased NCF between different sensors deployed at different locations. The effectiveness of our method is verified through a real data example.
The inconsistency of land use along the 10 m river buffer of East Kalibaru, Jakarta

The East Kalibaru River extends from Depok/South Jakarta to northern Jakarta. Visually, the riverbank is crowded with settlements, even though the Ministerial Regulation of Public Works and Housing Number 28 Years 2015 has regulated the River Boundary Line, where rivers must have a 10 m wide buffer zone. This study aims to reveal the inconsistency of land use along the 10 m river buffer of East Kalibaru using a quantitative and qualitative descriptive approach using spatial data, river hydrology, and river water quality status for the analysis process. The river was categorized into three segments (upstream, midstream, and downstream). Using ArcGIS, delineation was carried out along the 10 m river buffer of East Kalibaru and then overlaid with land use data, resulting in land use type suitability. Land use suitability was evaluated by calculating the percentage of land area based on compliance with the regulations. The inconsistency of land use along the 10 m river buffer of East Kalibaru amounted to 46.25% (26.21 ha). The most significant land use inconsistency occurred in the midstream segment (68.24% or 13.23 ha), whereas the best was found in the downstream segment (26.54% or 4.36 ha). Residential and office & trade land use types dominate the inconsistency of land use. Residential areas are mainly found in the midstream segment, with an area reaching 47.42% or 9.19 ha. The government should gradually be disciplined the 46.25% inconsistent area because the river buffers must have 100% suitable land use to optimize the function of the river boundary.
State of the Science and Recommendations for Using Wearable Technology in Sleep and Circadian Research.

Wearable sleep-tracking technology is of growing use in the sleep and circadian fields, including for applications across other disciplines, inclusive of a variety of disease states. Patients increasingly present sleep data derived from their wearable devices to their providers and the ever-increasing availability of commercial devices and new-generation research/clinical tools has led to the wide adoption of wearables in research, which has become even more relevant given the discontinuation of the Philips Respironics Actiwatch. Standards for evaluating the performance of wearable sleep-tracking devices have been introduced and the available evidence suggests that consumer-grade devices exceed the performance of traditional actigraphy in assessing sleep as defined by polysomnogram. However, clear limitations exist, for example, the misclassification of wakefulness during the sleep period, problems with sleep tracking outside of the main sleep bout or nighttime period, artifacts, and unclear translation of performance to individuals with certain characteristics or comorbidities. This is of particular relevance when person-specific factors (like skin color or obesity) negatively impact sensor performance with the potential downstream impact of augmenting already existing healthcare disparities. However, wearable sleep-tracking technology holds great promise for our field, given features distinct from traditional actigraphy such as measurement of autonomic parameters, estimation of circadian features, and the potential to integrate other self-reported, objective and passively recorded health indicators. Scientists face numerous decision points and barriers when incorporating traditional actigraphy, consumer-grade multi-sensor devices, or contemporary research/clinical-grade sleep trackers into their research. Considerations include wearable device capabilities and performance, target population and goals of the study, wearable device outputs and availability of raw and aggregate data, and data extraction, processing, and analysis. Given the difficulties in the implementation and utilization of wearable sleep-tracking technology in real-world research and clinical settings, the following State of the Science review requested by the Sleep Research Society aims to address the following questions. What data can wearable sleep-tracking devices provide? How accurate are these data? What should be taken into account when incorporating wearable sleep-tracking devices into research? These outstanding questions and surrounding considerations motivated this work, outlining practical recommendations for using wearable technology in sleep and circadian research.
Fusion of Hyperspectral Images and Digital Surface Models for Urban Object Extraction

The topic of this thesis is the usage of hyperspectral images and digital surface models for urban object extraction. A method for rectilinear building polygon extraction is proposed, which accounts for edge probabilities from both datasets. The edge probabilities are detected in a linear scale space and combined by a Bayesian fusion. They are introduced as weights in the adjustment of building polygons. A new quality measure for the evaluation of the extracted building polygons, named PoLiS metric, is defined and compared to the community accepted measures.
Recent Advances in the Development of Monoclonal Antibodies and Next-Generation Antibodies

Abstract mAbs are highly indispensable tools for diagnostic, prophylactic, and therapeutic applications. The first technique, hybridoma technology, was based on fusion of B lymphocytes with myeloma cells, which resulted in generation of single mAbs against a specific Ag. Along with hybridoma technology, several novel and alternative methods have been developed to improve mAb generation, ranging from electrofusion to the discovery of completely novel technologies such as B cell immortalization; phage, yeast, bacterial, ribosome, and mammalian display systems; DNA/RNA encoded Abs; single B cell technology; transgenic animals; and artificial intelligence/machine learning. This commentary outlines the evolution, methodology, advantages, and limitations of various mAb production techniques. Furthermore, with the advent of next-generation Ab technologies such as single-chain variable fragments, nanobodies, bispecific Abs, Fc-engineered Abs, Ab biosimilars, Ab mimetics, and Ab-drug conjugates, the healthcare and pharmaceutical sectors have become resourceful to develop highly specific mAb treatments against various diseases such as cancer and autoimmune and infectious diseases.
The pathogenic role of metabolism in Sjögren's syndrome.

The link between immune cell function and cell metabolic reprogramming is currently known under the term "immunometabolism". Similarly to the Warburg's effect described in cancer cells, in activated immune cells an up-regulation of specific metabolic pathways has been described and seems to be pathogenic in different inflammatory conditions. Sjӧgren's syndrome (SS) is a systemic autoimmune disease that affects the exocrine glands and is characterised by a progressive loss of secretory function. Despite the increasing amount of evidence on the ability of metabolism in regulating cell behaviour in inflammatory or tumoral conditions, the field of metabolism in SS is still for the most part unexplored.The aim of this review is to summarise currently available studies evaluating cell metabolism in SS with a particular focus on the possible pathogenic role of metabolic changes in immune and non-immune cells in this condition.
PRAME Expression: A Target for Cancer Immunotherapy and a Prognostic Factor in Uveal Melanoma

Purpose Uveal melanoma (UM) is a rare disease with a high mortality, and new therapeutic options are being investigated. Preferentially Expressed Antigen in Melanoma (PRAME) is a cancer testis antigen, expressed in the testis, but also in cancers, including uveal melanoma. PRAME is considered a target for immune therapy in several cancers, and PRAME-specific T cell clones have been shown to kill UM cells. Methods We studied the literature on PRAME expression in hematological and solid malignancies, including UM, and its role as a target for immunotherapy. The distribution of tumor features was compared between PRAME-high and PRAME-low UM in a 64-patient cohort from the Leiden University Medical Center (LUMC) and in the Cancer Genome Atlas (TCGA) cohort of 80 cases and differential gene expression analysis was performed in the LUMC cohort. Results PRAME is expressed in many malignancies, it is frequently associated with a negative prognosis, and can be the target of T cell receptor (TCR)-transduced T cells, a promising treatment option with high avidity and safety. In UM, PRAME is expressed in 26% to 45% of cases and is correlated with a worse prognosis. In the LUMC and the TCGA cohorts, high PRAME expression was associated with larger diameter, higher Tumor-Node-Metastasis (TNM) stage, more frequent gain of chromosome 8q, and an inflammatory phenotype. Conclusions We confirm that PRAME is associated with poor prognosis in UM and has a strong connection with extra copies of 8q. We show that PRAME-specific immunotherapy in an adjuvant setting is promising in treatment of malignancies, including UM.
P-V-T measurements of iron suicide (ε-FeSi) Implications for silicate-metal interactions in the early Earth

We have measured the high-pressure high-temperature equation of state of iron silicide (E-FeSi) by synchrotron X-ray diffraction, in-situ in a multi-anvil apparatus. Analysis of the non-hydrostatic stress-free data yielded the following thermoelastic parameters: Vo = 90.39(4) A3, Ko = 172(3) GPa, (dK/dT)p = -0.043(8) GPaK-I, a = 5.1(4) 10-5 K-I with fixed K'o = 4. Discrepancies with previous ultrasonic measurements could be explained by highly anharmonic effects in this compound. These equation-of-state parameters were included in a thermodynamic model of the reaction between Fe and SiOz, showing that the reduction of the silicates by iron presents a maximum at pressures between 8 and 15 GPa, and could be efficient at high temperatures, depending on the values of the activity coefficient of silicon in Fe-Si alloys. Similar reduction reactions in the Earth's complex system would have profound implications for the compositions of mantle and core, as weil as for reactions at the core-mantle boundary. Key-words: high-press ure experiments, equations of state, XRD data, early Earth.
Smart Measuring Instruments for Cyber-Physical Systems

Aiming the substantial development of Cyber- Physical systems, which are becoming a key element of everyday life, the smart measuring instruments are considered below as the indispensable part of entire systems. Verification of the metrological subsystems for parameters determining the controlled equipment and processes through the development, implementation and realization of specific metrology and standardization methods, instruments, that is successfully described by the terms “metrological hardware, software, and middleware”.
ASCC3 promotes the immunosuppression and progression of non-small cell lung cancer by impairing the type I interferon response via CAND1-mediated ubiquitination inhibition of STAT3

Background Activating signal cointegrator 3 (ASCC3) has been identified as an oncogenic factor that impairs host immune defense. However, the underlying mechanisms of carcinogenesis and its impact on the antitumor immune response remain unclear. In this study, we aimed to investigate the molecular mechanisms of ASCC3 in the progression of non-small cell lung cancer (NSCLC). Methods Single-cell sequencing data from the Gene Expression Omnibus and gene expression profiles from The Cancer Genome Atlas database were analyzed. The expression, clinical relevance and biological functions of ASCC3 in NSCLC were explored. Then, RNA sequencing, immunoprecipitation, mass spectrometry, immunofluorescence, and flow cytometry analyses were conducted to explore the underlying molecular mechanisms. In addition, in vivo experiments in mouse models were conducted to explore the probability of ASCC3 knockdown to improve the efficacy of anti-Programmed Death-1 (PD-1) therapy in NSCLC. Results ASCC3 was significantly upregulated in NSCLC and correlated with poor pathological characteristics and prognosis in patients with NSCLC. Overexpression of ASCC3 promoted malignant phenotypes of NSCLC cells and induced an immunosuppressive tumor microenvironment, which was characterized by a decrease in CD8+ T cells, natural killer cells and dendritic cells but an increase in regulatory T(Treg) cells. Mechanistically, ASCC3 stabilized signal transducer and activator of transcription (STAT)3 signaling by recruiting Cullin-associated and neddylation dissociated 1 (CAND1), which inhibited ubiquitin-mediated degradation of STAT3, thereby impairing the type I interferon response of tumor cells and promoting the immunosuppression and progression of NSCLC. Furthermore, high expression of ASCC3 impaired the efficacy of anti-PD-1 therapy, and an anti-PD-1 antibody combined with ASCC3 knockdown exerted promising synergistic efficacy in a preclinical mouse model. Conclusion ASCC3 could stabilize the STAT3 pathway via CAND1, reshaping the tumor microenvironment and inducing resistance to anti-PD-1 therapy, which promotes the progression of NSCLC. It is a reliable prognostic indicator and can be a target in combination therapy for NSCLC.