Miracle-dz/UniFAR-FTUs huggingface dataset:
Dark Energy and Dark Matter from Rute as Different Manifestations of Vacuum Energy

Dark energy and dark matter are described as different manifestations of vacuum energy within Rute’s framework of dimensional symmetry and gravity. In this framework, the bare vacuum energy component exists in a gravitationally inert state where actual gravitational constant G o = 0G , while real particles oscillates between this inert state and the active state where G o = 2G . The background effect of neutrino substrates in the inert state makes G o > 0G in such state, causing the gravitation of virtual particles with positive pressure appearing as hot and cold dark matter. A non zero component of vacuum energy from the inert state also spills into the gravitationally active state as a cosmological constant form of dark energy. This is due to an energy density constraint and speed limit asymmetry between the two gravitational states that limits the capacity of the inert state to contain all the vacuum energy component. This form of dark energy and dark matter, are parameterized by a common asymmetry parameter Γ which is suppressed in deep gravitational potential wells. The dynamics of this form of dark matter however, is complicated by the flavour and energy dependent parameters of its neutrino substrate resulting in the existence of heavy and light dark matter categories. Rute predicts a curvature supressed Gravitational Wave Reheating (GWR) mechanism in which gravitational waves produce electromagnetic secondaries in the presence of negative pressure such as that from strong magnetic fields and even dark energy. This mechanism may explain Fast Radio Bursts (FRBs) and some other mystery radio signals. Two space based experiments to test GWR and to detect heavy dark matter are briefly discussed.
Lipo-chitooligosaccharide and thuricin 17 act as plant growth promoters and alleviate drought stress in Arabidopsis thaliana

Lipo-chito-oligosaccharide (LCO–from Bradyrhizobium japonicum) and thuricin 17 (Th17–from Bacillus thuringiensis) are bacterial signal compounds from the rhizosphere of soybean that have been shown to enhance plant growth in a range of legumes and non-legumes. In this study, an attempt to quantify phytohormones involved in the initial hours after exposure of Arabidopsis thaliana to these compounds was conducted using UPLC-ESI-MS/MS. A petri-plate assay was conducted to screen for drought stress tolerance to PEG 8000 infusion and plant growth was studied 21-days post-stress. Arabidopsis thaliana plants grown in trays with drought stress imposed by water withhold were used for free proline determination, elemental analysis, and untargeted proteomics using LC-MS/MS studies. At 24 h post-exposure to the signal compounds under optimal growth conditions, Arabidopsis thaliana rosettes varied in their responses to the two signals. While LCO-treated rosettes showed a decrease in total IAA, cytokinins, gibberellins, and jasmonic acid, increases in ABA and SA was very clear. Th17-treated rosettes, on the other hand, showed an increase in IAA and SA. Both treatments resulted in decreased JA levels. Under severe drought stress imposed by PEG 8000 infusion, LCO and Th17 treatments were found to significantly increase fresh and dry weight over drought-stressed control plates, indicating that the presence of the signaling compounds decreased the negative effects experienced by the plants. Free proline content increased in LCO- and Th17-treated plants after water-withhold drought stress. Elemental analysis showed a significant increase in carbon percentage at the lower concentration of Th17. Untargeted proteomics revealed changes in the levels of drought-specific ribosomal proteins, glutathione S-transferase, late embryogenesis proteins, vegetative storage proteins 1 and 2, thaumatin-like proteins, and those related to chloroplast and carbon metabolism. The roles of some of these significantly affected proteins detected under drought stress are discussed.
Towards Identifying Social Bias in Dialog Systems: Frame, Datasets, and Benchmarks

Warning: this paper contains content that may be offensive or upsetting. The research of open-domain dialog systems has been greatly prospered by neural models trained on large-scale corpora, however, such corpora often introduce various safety problems (e.g., offensive languages, biases, and toxic behaviors) that signiﬁcantly hinder the deployment of dialog systems in practice. Among all these unsafe issues, addressing social bias is more complex as its negative impact on marginalized populations is usually expressed implicitly, thus requiring normative reasoning and rigorous analysis. In this paper, we focus our investigation on social bias detection of dialog safety problems. We ﬁrst propose a novel D IAL - B IAS F RAME for analyzing the social bias in conversations pragmatically, which considers more comprehensive bias-related analyses rather than simple dichotomy annotations. Based on the proposed framework, we further introduce CD AIL -B IAS D ATASET that, to our knowledge, is the ﬁrst well-annotated Chinese social bias dialog dataset. In addition, we establish several dialog bias detection benchmarks at different label granularities and input types (utterance-level and context-level). We show that the proposed in-depth analyses together with these benchmarks in our D IAL - B IAS F RAME are necessary and essential to bias detection tasks and can beneﬁt building safe dialog systems in practice.
Temporal and Spatial Variations of Precipitation in South Korea for Recent 30 Years (1976-2005) and Geographic Environments

Temporal and spatial variations of precipitation in South Korea are investigated using 60 observation data of the recent 30-years from 1976 to 2005. The area averaged annual precipitation amount is about 1310 mm and shows a strong spatial variation, maximum at the southern and Kyoungki province (>1300 mm) and minimum at the Kyungpook province(100 days) and minimum at the Kyungpook province (
Physical Restraint Use in Nursing Homes—Regional Variances and Ethical Considerations: A Scoping Review of Empirical Studies

Background: Physical restraints are known to violate human rights, yet their use persists in long-term care facilities. This study aimed to explore the prevalence, methods, and interventions related to physical restraint use among the elderly in nursing homes. Methods: The method described by Joanna Briggs was followed to conduct a scoping review without a quality assessment of the selected studies. An electronic search was conducted to find eligible empirical articles using MEDLINE, PsycINFO, EMBASE, Web of Science, Scopus, Google Scholar, CINAHL, and grey literature. The database search was performed using EndNote software (version X9, Clarivate Analytics), and the data were imported into Excel for analysis. Results: The prevalence of physical restraint use was found to be highest in Spain (84.9%) and lowest in the USA (1.9%). The most common device reported was bed rails, with the highest prevalence in Singapore (98%) and the lowest (4.7%) in Germany, followed by chair restraint (57%). The largest number of studies reported the prevention and/or risk of falls to be the main reason for using physical restraints, followed by behavioral problems such as wandering, verbal or physical agitation, and cognitive impairment. Most studies reported guideline- and/or theory-based multicomponent interventions consisting of the training and education of nursing home staff. Conclusions: This review provides valuable insights into the use of physical restraints among elderly residents in nursing homes. Despite efforts to minimize their use, physical restraints continue to be employed, particularly with elderly individuals who have cognitive impairments. Patient-related factors such as wandering, agitation, and cognitive impairment were identified as the second most common reasons for using physical restraints in this population. To address this issue, it is crucial to enhance the skills of nursing home staff, especially nurses, in providing safe and ethical care for elderly residents with cognitive and functional impairments, aggressive behaviors, and fall risks.
Antennas and Propagation Research From Large-Scale Unstructured Data With Machine Learning: A review and predictions

The past century has witnessed remarkable progress in antennas and propagation (A&P) research, which has made dramatic changes to our society and life and has led to paradigm shifts in engineering and technology. Although the underlying theory of electromagnetics is well established and mature, research on A&P will continue to play a paramount role in the Fourth Industrial Revolution. In this article, we present an approach based on natural language processing (NLP) and machine learning (ML) techniques to review A&P research based on large-scale unstructured data from openly published scientific papers and patents and, in turn, provide meaningful summative and predictive information. We particularly screen 159,000 research papers published between 1981 and 2021 and extract a pool of 2,415 significant keywords reflecting past and present key research topics in A&P. We then apply an encoder–decoder long short-term memory (LSTM) network with an integrated attention mechanism to predict the future trends of A&P research in the form of a Gartner’s hype cycle.
Monoclonal antibodies binding to different epitopes of CD20 differentially sensitize DLBCL to different classes of chemotherapy

Introduction Rituximab (R), an anti-CD20 monoclonal antibody (mAb) and the world’s first approved antibody for oncology patients, was combined with the CHOP chemotherapy regimen and markedly improved the prognosis of all B- cell–derived lymphomas, the most common hematological malignancy worldwide. However, there is a 35% disease recurrence with no advancement in the first-line treatment since R was combined with the archetypal CHOP chemotherapy regimen nearly 30 years ago. There is evidence that R synergizes with chemotherapy, but the pharmacological interactions between R and CHOP or between newer anti-CD20 mAbs and CHOP remain largely unexplored. Methods We used in vitro models to score pharmacological interactions between R and CHOP across various lymphoma cell lines. We compared these pharmacological interactions to ofatumumab, a second-generation anti-CD20 mAb, and CHOP. Lastly, we used RNA-sequencing to characterize the transcriptional profiles induced by these two antibodies and potential molecular pathways that mediate their different effects. Results We discovered vast heterogeneity in the pharmacological interactions between R and CHOP in a way not predicted by the current clinical classification. We then discovered that R and ofatumumab differentially synergize with the cytotoxic and cytostatic capabilities of CHOP in separate distinct subsets of B-cell lymphoma cell lines, thereby expanding favorable immunochemotherapy interactions across a greater range of cell lines beyond those induced by R-CHOP. Lastly, we discovered these two mAbs differentially modulate genes enriched in the JNK and p38 MAPK family, which regulates apoptosis and proliferation. Discussion Our findings were completely unexpected because these mAbs were long considered to be biological and clinical equivalents but, in practice, may perform better than the other in a patient-specific manner. This finding may have immediate clinical significance because both immunochemotherapy combinations are already FDA-approved with no difference in toxicity across phase I, II, and III clinical trials. Therefore, this finding could inform a new precision medicine strategy to provide additional therapeutic benefit to patients with B-cell lymphoma using immunochemotherapy combinations that already meet the clinical standard of care.
Chemometric Classification of Mangifera indica L. Leaf Cultivars, Based on Selected Phytochemical Parameters; Implications for Standardization of the Pharmaceutical Raw Materials

Introduction Mangifera indica leaves are among the most common materials employed in manufacturing herbal medicinal products. Despite the phytochemical variation of M. indica cultivars, there are no monographs to guide the cultivation, processing, and authentication of the materials. Methods This study characterized 15 Ugandan M. indica leaf varieties, with reference to extraction index (EI), total phenolic content (TPC), antioxidant activity (AOA), and mangiferin concentration (MC). In addition, HPLC fingerprints were established to evaluate the overall phytoequivalence of the materials. Then, using hierarchical clustering (HC) and principal component analysis (PCA), the materials were assigned quality grades. Results The mean EI was 9.39 ± 1.64% and varied among the varieties (P=0.001); the TPC varied significantly (P < 0.0001), from 183.29 ± 2.36 mg/g (Takataka) to 79.47 ± 0.58 mg/g (Apple mango). AOA ranged from 16.81 ± 2.85 μg/mL (Doodo red) to 87.85 μg/mL (Asante). MC varied significantly (P < 0.0001), from 105.75 ± 0.60 mg/g (Kate) to 39.53 ± 0.30 mg/g (Asante). HC gave four major grades: A to D (A, varieties with the highest TPC, MC, and AOA). These parameters reduced to below average from group B to group D. The chromatographic fingerprints were visually similar, but the number of peaks varied, from 19 (Kawanda green) to 29 (Kawanda wide), with 23.5 ± 2.9 average peaks. Whole fingerprints were less similar (r < 0.8) than common peak fingerprints (r > 0.9, P < 0.001). PCA grouped the fingerprints into five clusters; loading plots for PC 1 and 2 revealed two important compounds, one at Rt = 15.828 minutes (mangiferin) and the other at 6.021 minutes. Using the standardized common fingerprints, unknown field samples clustered closely with Koona, Kate, and Kawanda green varieties. Conclusions The EI, TPC, MC, and AOA values can be utilized to monitor consistency in the quality of materials and the production process. The grades generated can be used to select materials for cultivation and manufacturing. Where minimum concentrations are set, materials of different concentrations are used to dilute or concentrate each other. The HPLC fingerprints can be utilized to authenticate the materials. More samples from different agroecological regions of the country should be tested to cater to climatic variations in order to develop GMP-compliant botanical identification methods.
Reduced Plasma Guanylin Levels Following Enterotoxigenic Escherichia coli-Induced Diarrhea

The intestinal peptide hormones guanylin (GN) and uroguanylin (UGN) interact with the epithelial cell receptor guanylate cyclase C to regulate fluid homeostasis. Some enterotoxigenic Escherichia coli (ETEC) produce heat-stable enterotoxin (ST), which induces diarrhea by mimicking GN and UGN. Plasma concentrations of prohormones of GN (proGN) and UGN (proUGN) are reportedly decreased during chronic diarrheal diseases. Here we investigate whether prohormone concentrations also drop during acute diarrhea caused by ST-producing ETEC strains TW10722 and TW11681. Twenty-one volunteers were experimentally infected with ETEC. Blood (n = 21) and urine (n = 9) specimens were obtained immediately before and 1, 2, 3, and 7 days after ETEC ingestion. Concentrations of proGN and proUGN were measured by ELISA. Urine electrolyte concentrations were measured by photometry and mass spectrometry. Ten volunteers developed diarrhea (D group), and eleven did not (ND group). In the D group, plasma proGN, but not proUGN, concentrations were substantially reduced on days 2 and 3, coinciding with one day after diarrhea onset. No changes were seen in the ND group. ETEC diarrhea also seemed to affect diuresis, the zinc/creatinine ratio, and sodium and chloride secretion levels in urine. ETEC-induced diarrhea causes a reduction in plasma proGN and could potentially be a useful marker for intestinal isotonic fluid loss.
Levels of Myostatin, Adiponectin and Lipid Profile in Hyperlipidemia Patients

Background: Excess fat is one of the biggest risk factors for the development of heart disease and one of the top five leading causes of death. The researchers expect from their study that deaths due to cardiovascular diseases will increase from (17.3) million cases in 2017 to (23.6) million deaths by 2030. Aim: Determination of the concentration of lipid profile variables (TC, TG, HDL-C, LDL-C, VLDL-C). Estimating the concentration of some hormones such as myostatin and adiponectin in the serum of study samples in males and females with hyperlipidemia at different ages. Materials and methods: The study included collecting (90) samples and dividing them into two groups (20-60). Blood samples were collected from the vein (10ml) using medical syringes, and the blood was placed in plastic tubes, where the samples were left for (15-20) minutes at a temperature of 37 °C in a water bath until the blood coagulated, and then the samples were separated in a centrifuge. Results: the results showed a significant increase in each of TC, TG, LDL and VLDL, and a significant decrease in Myostatin and HDL, while the results showed no significant difference in Adiponectin. In females compared to healthy subjects the results showed a significant increase in TC, TG, LDL, and VLDL, and the results showed a significant decrease in HDL, while the results showed that there was no significant difference in both Adiponectin and Myostatin. Conclusions: We conclude from our current study that hyperlipidemia is associated with an imbalance in the level of muscular lipid movements and is therefore considered a risk factor for the occurrence of cardiovascular diseases and requires follow-up and a healthy diet with treatment.
CoMod: An Abstractive Approach to Discourse Context Identification

Generative text summarization can condense large volumes of information into a concise summary. It helps users quickly grasp the main points of a text without having to read the entire document. Machine learning (ML) plays a pivotal role in this domain, offering significant advantages in information processing and comprehension. In this paper we present CoMod, an abstractive method for generating the context of a document, from its content and that of the referenced documents, if any. CoMod analyzes the intricate patterns and relationships within a document’s content, thereby extracting and inferring the underlying context. The context generation process involves using a word linearization process as well as a Markov model, specifically a Bigram model, to predict the likelihood of word sequences. The Markov model is trained on a corpus of text and used to generate coherent sentences based on the probabilities of transitioning from one word to another. Markov tables allows to adapt the generated context to a specific domain and can be built on the fly in CoMod. The approach was compared to other methods and demonstrated very encouraging capabilities by outperforming other approaches tested on the same datasets. It thus confirms the potential of generative methods in the field of automatic text summarization and their ability of leveraging the power of machine learning for context generation to revolutionize information management, boosting productivity, scalability and knowledge discovery in various domains.
Clinical Development and Evaluation of a Multi-Component Dissolving Microneedle Patch for Skin Pigmentation Disorders

Excessive melanin deposition in the skin leads to various skin pigmentation diseases, such as chloasma and age spots. The deposition is induced by several factors, including tyrosinase activities and ultraviolet-induced oxidative stress. Herein, we propose a multi-component, multi-pathway drug combination, with glabridin, 3-O-ethyl-L-ascorbic acid, and tranexamic acid employed as, respectively, a tyrosinase inhibitor, an antioxidant, and a melanin transmission inhibitor. Considering the poor skin permeability associated with topical application, dissolving microneedles (MNs) prepared with hyaluronic acid/poly(vinyl alcohol)/poly(vinylpyrrolidone) were developed to load the drug combination. The drug-loaded microneedles (DMNs) presented outstanding skin insertion, dissolution, and drug delivery properties. In vitro experiments confirmed that DMNs loaded with active ingredients had significant antioxidant and inhibitory effects on tyrosinase activity. Furthermore, the production of melanin both in melanoma cells (B16-F10) and in zebrafish was directly reduced after using DMNs. Clinical studies demonstrated the DMNs’ safety and showed that they have the ability to effectively reduce chloasma and age spots. This study indicated that a complex DMN based on a multifunctional combination is a valuable depigmentation product worthy of clinical application.
Holocene climate variability in the Norwegian current and North Cape current inferred from benthic stable isotope records

ii Abstract The Malangenfjord, with its deep sill and good hydrological communication with the Norwegian Sea, has been the site for a high resolution paleoclimatic investigation. By using benthic foraminifera and stable isotopes from a marine sediment core, this study will reconstruct the changes in inflow of warm Atlantic Water at a high-latitude setting. Radiocarbon dating has given ages between 8000 – 1500 cal. yrs BP. The benthic δ 18 O values increases from 1.8‰ to 3‰ in the period from 8 to 1.5 cal. kyr yr BP. Interpretations indicate that this isotopic enrichment reflects a drop in the bottom water temperature from 10°C to 5.5°C, the latter being around 1.5°C colder than the modern temperature in the Malangenfjord. Additional data was retrieved from Ingøydjupet in the southern Barents Sea, in order to investigate the paleoclimatic changes in the North Cape Current. This record ranging from 15000 – 0 cal. yrs BP, has to tolerate a low resolution and a highly uncertain age model compared to the record from the Malangenfjord. Nevertheless it displays a deglacial unstable period, thermal optimum and a later enrichment in the benthic δ 18 O values from 2.8‰ to 3.6‰. The preliminary interpretation suggests a late Holocene cooling with bottom water temperatures dropping from 6°C to 2.5°C, the latter being 1.5°C colder than modern temperature for the area. The study gives evidence for a long-term cooling with rapid changes superimposed on the general trend. The overall cooling trend correlates with the decreasing insolation at 70°N and isotopic data from the North GRIP ice core project. Several cold events could be interpreted as periods with reduced inflow of Atlantic Water, and vice versa for warmer events.