Miracle-dz/UniFAR-FTUs huggingface dataset:
The Conjugates of Indolo[2,3-b]quinoline as Anti-Pancreatic Cancer Agents: Design, Synthesis, Molecular Docking and Biological Evaluations

New amide conjugates of hydroxycinnamic acids (HCAs) and the known antineoplastic 5,11-dimethyl-5H-indolo[2,3-b]quinoline (DiMIQ), an analog of the natural alkaloid neocryptolepine, were synthesized and tested in vitro for anticancer activity. The compound 9-[((2-hydroxy)cinnamoyl)amino]-5,11-dimethyl-5H-indolo[2,3-b]quinoline (2), which contains the ortho-coumaric acid fragment, demonstrated dose-dependent effectiveness against both normal BxPC-3 and metastatic AsPC-1 pancreatic cancer cells. The IC50 values for AsPC-1 and BxPC-3 were 336.5 nM and 347.5 nM, respectively, with a selectivity index of approximately 5 for both pancreatic cancer cells compared to normal dermal fibroblasts. Conjugate 2 did not exhibit any hemolytic activity against human erythrocytes at the tested concentration. Computational studies were performed to predict the pharmacokinetic profile and potential mechanism of action of the synthesized conjugates. These studies focused on the ADME properties of the conjugates and their interactions with DNA, as well as DNA–topoisomerase alpha and beta complexes. All of the conjugates studied showed approximately one order of magnitude stronger binding to DNA compared to the reference DiMIQ, and approximately two orders of magnitude stronger binding to the topoisomerase II–DNA complex compared to DiMIQ. Conjugate 2 was predicted to have the strongest binding to the enzyme–DNA complex, with a Ki value of 2.8 nM.
Spatial Variations in the Abundance and Chemical Speciation of Phosphorus across the River–Sea Interface in the Northern Beibu Gulf

Water samples were collected to measure dissolved and particulate phosphorus species in order to examine the dynamics of phosphorus in the water column across the river–sea interface from the lower Dafengjiang River to the open Beibu Gulf. Dissolved inorganic phosphorus concentrations were as high as 0.90 ± 0.42 μM in river water but decreased dramatically to as low as 0.02 ± 0.01 μM in open coastal waters. Total dissolved phosphorus was largely measured in the form of dissolved inorganic phosphorus in river waters (58% ± 18%), whereas dissolved organic phosphorus became the predominant species (>90% on average) in open coastal waters. Total dissolved phosphorus was the dominant species, comprising 76% ± 16% of the total phosphorus, while total particulate phosphorus only comprised 24% ± 16% of the total phosphorus pool. Riverine inputs, physical and biological processes, and particulate phosphorus regeneration were the dominant factors responsible for the dynamic variations of phosphorus species in the study area. Based on a two-end-member mixing model, the biological uptake resulted in a dissolved inorganic phosphorus depletion of 0.12 ± 0.08 μM in the coastal surface water, whereas the replenishment of dissolved inorganic phosphorus in the lower river from particle P regeneration and release resulted in an increase (0.19 ± 0.22 μM) of dissolved inorganic phosphorus in the estuarine mixing region. The molar ratios of dissolved inorganic nitrogen to dissolved inorganic phosphorus and dissolved silicate to dissolved inorganic phosphorus in the open surface waters were >22, suggesting that, although the lower Dafengjiang River contained elevated concentrations of dissolved inorganic phosphorus, the northern Beibu Gulf was an overall P-limited coastal ecosystem.
Application of Semi-Supervised Learning in Image Classification: Research on Fusion of Labeled and Unlabeled Data

Deep learning has attracted wide attention recently because of its excellent feature representation ability and end-to-end automatic learning method. Especially in clinical medical imaging diagnosis, the semi-supervised deep learning model is favored and widely used because it can make maximum use of a limited number of labeled data and combine it with a large number of unlabeled data to extract more information and knowledge from it. However, the scarcity of medical image data, the vast image size, and the instability of image quality directly affect the model’s robustness, generalization, and image classification performance. Therefore, this paper proposes a new semi-supervised learning model, which uses quadratic neurons instead of traditional neurons, aiming to use quadratic convolution instead of the conventional convolution layer to improve the feature extraction ability of the model. In addition, we introduce two Dropout layers and two fully connected layers at the end of the model to enhance the nonlinear fitting ability of the network. Experiments on two large medical public data sets - ISIC 2019 and Retinopathy OCT - show that our method can improve the model’s generalization performance and image classification accuracy.
Thiophene Stability in Photodynamic Therapy: A Mathematical Model Approach

Thiophene-containing photosensitizers are gaining recognition for their role in photodynamic therapy (PDT). However, the inherent reactivity of the thiophene moiety toward singlet oxygen threatens the stability and efficiency of these photosensitizers. This study presents a novel mathematical model capable of predicting the reactivity of thiophene toward singlet oxygen in PDT, using Conceptual Density Functional Theory (CDFT) and genetic programming. The research combines advanced computational methods, including various DFT techniques and symbolic regression, and is validated with experimental data. The findings underscore the capacity of the model to classify photosensitizers based on their photodynamic efficiency and safety, particularly noting that photosensitizers with a constant rate 1000 times lower than that of unmodified thiophene retain their photodynamic performance without substantial singlet oxygen quenching. Additionally, the research offers insights into the impact of electronic effects on thiophene reactivity. Finally, this study significantly advances thiophene-based photosensitizer design, paving the way for therapeutic agents that achieve a desirable balance between efficiency and safety in PDT.
Governance of ecosystem services on small islands: three contrasting cases for St. Eustatius in the Dutch Caribbean

Natural ecosystems provide an attractive focus for tourism on small islands. However, at the same time tourism and other human actions can be detrimental to these ecosystems especially because governance of the ecosystem may be difficult due to the limited resilience of small island ecosystems. In this paper, we focus on the conditions under which self-governance will be the appropriate governance mechanism of ecosystem services on small islands. We apply Ostrom’s (2009) framework for common-pool resources in a socialecological system, and select the relevant indicators for small islands. We scored these indicators for three cases (environmental issues) in St. Eustatius, a Caribbean island under Dutch rule. These cases show that self-organization of ecosystem services is not an outcome easily achieved. The unevenly distributed benefits of potential measures are found to decrease community support of measures that could reinforce these ecosystem services.
Double jeopardy in astronomy and planetary science: Women of color face greater risks of gendered and racial harassment

Women generally, and women of color specifically, have reported hostile workplace experiences in astronomy and related fields for some time. However, little is known of the extent to which individuals in these disciplines experience inappropriate remarks, harassment, and assault. We hypothesized that the multiple marginality of women of color would mean that they would experience a higher frequency of inappropriate remarks, harassment, and assault in the astronomical and planetary science workplace. We conducted an internet‐based survey of the workplace experiences of 474 astronomers and planetary scientists between 2011 and 2015 and found support for this hypothesis. In this sample, in nearly every significant finding, women of color experienced the highest rates of negative workplace experiences, including harassment and assault. Further, 40% of women of color reported feeling unsafe in the workplace as a result of their gender or sex, and 28% of women of color reported feeling unsafe as a result of their race. Finally, 18% of women of color, and 12% of white women, skipped professional events because they did not feel safe attending, identifying a significant loss of career opportunities due to a hostile climate. Our results suggest that the astronomy and planetary science community needs to address the experiences of women of color and white women as they move forward in their efforts to create an inclusive workplace for all scientists.
Probabilistic inference of subsurface heterogeneity and interface geometry using geophysical data

Geophysical methods provide remotely sensed data that are sensitive to subsurface properties and interfaces. Knowledge about discontinuities is important throughout the Earth sciences: for example, the saltwater/freshwater interface in coastal areas drive mixing processes; the temporal development of the discontinuity between frozen and unfrozen ground is indicative of permafrost development; and the regolith-bedrock interface often plays a predominant role in both landslide and critical-zone investigations. Accurate detection of subsurface boundaries and their geometry is challenging when using common inversion routines that rely on smoothness constraints that smear out any naturally occurring interfaces. Moreover, uncertainty quantification of interface geometry based on such inversions is very difficult. In this paper, we present a probabilistic formulation and solution to the geophysical inverse problem of inferring interfaces in the presence of significant subsurface heterogeneity. We implement an empirical-Bayes-within-Gibbs formulation that separates the interface and physical property updates within a Markov chain Monte Carlo scheme. Both the interface and the physical properties of the two sub-domains are constrained to favour smooth spatial transitions and pre-defined property bounds. Our methodology is demonstrated on synthetic and actual surface-based electrical resistivity tomography data sets, with the aim of inferring regolith-bedrock interfaces. Even if we are unable to achieve formal convergence of the Markov chains for all model parameters, we demonstrate that the proposed algorithm offers distinct advantages compared to manual- or algorithm-based interface detection using deterministic geophysical tomograms. Moreover, we obtain more reliable estimates of bedrock resistivity and its spatial variations.
Exploring the secrets of virus entry: the first respiratory syncytial virus carrying beta lactamase

Background Respiratory Syncytial Virus (RSV) presents a significant health threat, especially to young children. In-depth understanding of RSV entry mechanisms is essential for effective antiviral development. This study introduces an innovative RSV variant, featuring the fusion of the beta-lactamase (BlaM) enzyme with the RSV-P phosphoprotein, providing a versatile tool for dissecting viral entry dynamics. Methods Using the AlphaFold2 algorithm, we modeled the tertiary structure of the P-BlaM chimera, revealing structural similarities with both RSV-P and BlaM. Functional assessments, utilizing flow cytometry, quantified beta-lactamase activity and GFP expression in infected bronchial epithelial cells. Western blot analysis confirmed the integrity of P-BlaM within virions. Results The modeled P-BlaM chimera exhibited structural parallels with RSV-P and BlaM. Functional assays demonstrated robust beta-lactamase activity in recombinant virions, confirming successful P-BlaM incorporation as a structural protein. Quercetin, known for its antiviral properties, impeded viral entry by affecting virion fusion. Additionally, Ulixertinib, an ERK-1/2 inhibitor, significantly curtailed viral entry, implicating ERK-1/2 pathway signaling. Conclusions Our engineered RSV-P-BlaM chimera emerges as a valuable tool, illuminating RSV entry mechanisms. Structural and functional analyses unveil potential therapeutic targets. Quercetin and Ulixertinib, identified as distinct stage inhibitors, show promise for targeted antiviral strategies. Time-of-addition assays pinpoint quercetin’s specific interference stage, advancing our comprehension of RSV entry and guiding future antiviral developments.
The Clovis Lithic Assemblage from El Fin del Mundo, Sonora, Mexico: Evidence of Upland Campsite Localities

ABSTRACT El Fin del Mundo is a Clovis site located in the Sonoran Desert of northwest Mexico. The site has produced one of the largest assemblages of diagnostic Clovis stone tools south of the US-Mexico border. The Clovis lithic assemblage includes bifaces, unifaces, and blades. The artifact classes, tool types, and their contexts are indicative of a Clovis camp or camps where domestic tasks took place on the stable uplands surrounding a gomphothere (proboscidean) kill.
Mapping reference evapotranspiration from meteorological satellite data and applications

Reference evapotranspiration (ETo) is an agrometeorological variable widely used in hydrology and agriculture. The FAO-56 Penman-Monteith combination method (PM method) is a standard for computing ETo for water management. However, this scheme is limited to areas where climatic data with good quality are available. Maps of 10-day averaged ETo at 5 km × 5 km grid spacing for the Taiwan region were produced by multiplying pan evaporation (Epan), derived from ground solar radiation (GSR) retrieved from satellite images using the Heliosat-3 method, by a fixed pan coefficient (Kp). Validation results indicated that the overall mean absolute percentage error (MAPE) and normalized root-mean-square deviation (NRMSD) were 6.2 and 7.7%, respectively, when compared with ETo computed by the PM method using spatially interpolated 10-day averaged daily maximum and minimum temperature datasets and GSR derived from satellite inputs. Land coefficient (KL) values based on the derived ETo estimates and long term latent heat flux measurements, were determined for the following landscapes: Paddy rice (Oryza sativa), subtropical cypress forest (Chamaecyparis obtusa var. formosana and Chamaecyparis formosensis), warm-to-temperate mixed rainforest (Cryptocarya chinensis, Engelhardtia roxburghiana, Tutcheria shinkoensis, and Helicia formosana), and grass marsh (Brachiaria mutica and Phragmites australis). The determined land coefficients are indispensable to scale ETo in estimating regional evapotranspiration. Article history: Received 22 June 2016 Revised 8 November 2016 Accepted 15 November 2016
The Effects of Temperature on the Development and Survival of Bathycoelia distincta (Hemiptera: Pentatomidae), a Significant Pest of Macadamia in South Africa

Simple Summary Bathycoelia distincta poses a significant threat to the South African macadamia industry. Despite the acknowledged influence of temperature on insects, a comprehensive developmental biology investigation for B. distincta has not been undertaken to date. This study systematically presents empirical data on the effects of temperature on the developmental duration, survival, and developmental thresholds of B. distincta‘s life stages under constant temperatures. The findings of this study reveal that the thermal developmental range of this pest ranges from 13.5 to 38.0 °C, with an optimum temperature of 29.5 °C. Moreover, B. distincta requires 783 degree days to develop from an egg to the adult stage. Considering the prevailing global warming trends, the South African Macadamia industry may experience more damage due to a faster development at warmer temperatures. Abstract Temperature is the most influential condition affecting insect development and population dynamics. Understanding its impact and other important factors, such as diet, could provide fine-scale predictions of species abundance and distribution in space and time. The two-spotted stink bug, Bathycoelia distincta Distant (Hemiptera: Pentatomidae), is a significant pest of macadamia in South Africa for which limited information on developmental biology exists. Here, for the first time, variations in key developmental parameters of the B. distincta biology were studied systematically. The developmental duration, survival rate, development rate, lower developmental threshold (Tmin), optimum developmental threshold (Topt), upper developmental threshold (Tmax), and thermal constant were quantified for each developmental stage of B. distincta. In addition, the effect of diet (macadamia nut and sweetcorn) on the developmental duration and survival rate were quantified. This study was conducted at five constant temperatures (18, 21, 22, 25, and 29 °C) with relative humidity (RH) variations. The developmental duration from egg to adult decreased significantly with increased temperature: 21 °C (±60 days) to 29 °C (±32 days). The survival rate was significantly different for instar 2 between temperatures. Nymphs (instars 2 and 4) developed faster on the sweetcorn diet than on a macadamia diet, but the total developmental time did not differ significantly between the diets. Development from egg to adult required 783 degree days (DD), with a Tmin of 13.5 °C, Topt of 29.5 °C, and Tmax of 38 °C. Ongoing global warming will increase the population growth of B. distincta through increased development rate, resulting in more damage to macadamia nuts. Understanding the developmental biology and thresholds for the DD model of B. distincta is fundamental for predicting its phenology and outbreaks in macadamia orchards.
Asal Usul Formasi Savana: Tinjauan dari Nusa Tenggara Timur dan Hasil Penelitian di Baluran Jawa Timur [Origin of savanna formation: Literature review from East Nusa Tenggara and research results from Baluran East Java Indonesia]

Savannas are ecosystems mostly confined to tropical and subtropical regions that are characterized by a continuous cover of C4 grasses that have different characteristics based on seasonality and where woody plants are also an important feature, but with sparse cover and no closed canopy. This is common foramtion in the driest part of Indonesia such as East Nusa Tenggara (NTT), however savana can also be found in Java Island: Baluran Savanna in East Java. There has been considerable amount of debat among scientists, botanists in Indonesia regarding the origin of Indonesian savanna. Using literature study and also field observation at Baluran National Park, combined with remote sensing technique and multivariate data analysis, this research concluded that savanna in Baluran National Park is originated from the monsoon forest/dry forest surrounding the area. This is drawn based on three findings: the existence of distinct borders or boundaries between savannas and adjacent forests that have no correlation with changes in soil types. The occurrence of forest tree species in savannas and the swift regrowth of shrubs and trees species when fire and grazing is excluded is contributing to this assumption. Lastly is history or records of intentional burning and/or natural fires that also strengthen this hypothesis.
Maximum allowable hp rating of 3-phase induction motor fed through a stand-alone constant V/f controlled DFIG via RSC

This paper presents a scheme to start three-phase induction motors (IMs) directly connected to terminals of constant V/f controlled doubly fed induction generator (DFIG) through the rotor side converter (RSC). The proposed control is achieved by controlling the output voltage and frequency of stand-alone DFIG via controlling an injected voltage into the rotor circuit through the RSC. The control scheme provides a search for maximum rating of the three-phase IM which can be supplied from a DFIG. The search technique is based on using a simplified mathematical model to find the capability limits of the RSC and DFIG. It is found that these parameters depend on the stator frequency and rotor slip. Therefore, an investigation is performed to find the lowest frequency and the corresponding allowable maximum rating for the IM to be safely started. A typical example is provided in the paper for a 15 kW DFIG. It is shown that this generator could supply a three-phase IM with a maximum rating of 1-hp if it operated at nominal outputs, voltage and frequency, during start-up period. While, using the proposed technique, the same generator could start-up a three-phase IM with maximum power rating of 7.25 hp.
Application of Copper–Sulfur Compound Electrode Materials in Supercapacitors

Supercapacitors (SCs) are a novel type of energy storage device that exhibit features such as a short charging time, a long service life, excellent temperature characteristics, energy saving, and environmental protection. The capacitance of SCs depends on the electrode materials. Currently, carbon-based materials, transition metal oxides/hydroxides, and conductive polymers are widely used as electrode materials. However, the low specific capacitance of carbon-based materials, high cost of transition metal oxides/hydroxides, and poor cycling performance of conductive polymers as electrodes limit their applications. Copper–sulfur compounds used as electrode materials exhibit excellent electrical conductivity, a wide voltage range, high specific capacitance, diverse structures, and abundant copper reserves, and have been widely studied in catalysis, sensors, supercapacitors, solar cells, and other fields. This review summarizes the application of copper–sulfur compounds in SCs, details the research directions and development strategies of copper–sulfur compounds in SCs, and analyses and summarizes the research hotspots and outlook, so as to provide a reference and guidance for the use of copper–sulfur compounds.
An Innovative Inducer of Platelet Production, Isochlorogenic Acid A, Is Uncovered through the Application of Deep Neural Networks

(1) Background: Radiation-induced thrombocytopenia (RIT) often occurs in cancer patients undergoing radiation therapy, which can result in morbidity and even death. However, a notable deficiency exists in the availability of specific drugs designed for the treatment of RIT. (2) Methods: In our pursuit of new drugs for RIT treatment, we employed three deep learning (DL) algorithms: convolutional neural network (CNN), deep neural network (DNN), and a hybrid neural network that combines the computational characteristics of the two. These algorithms construct computational models that can screen compounds for drug activity by utilizing the distinct physicochemical properties of the molecules. The best model underwent testing using a set of 10 drugs endorsed by the US Food and Drug Administration (FDA) specifically for the treatment of thrombocytopenia. (3) Results: The Hybrid CNN+DNN (HCD) model demonstrated the most effective predictive performance on the test dataset, achieving an accuracy of 98.3% and a precision of 97.0%. Both metrics surpassed the performance of the other models, and the model predicted that seven FDA drugs would exhibit activity. Isochlorogenic acid A, identified through screening the Chinese Pharmacopoeia Natural Product Library, was subsequently subjected to experimental verification. The results indicated a substantial enhancement in the differentiation and maturation of megakaryocytes (MKs), along with a notable increase in platelet production. (4) Conclusions: This underscores the potential therapeutic efficacy of isochlorogenic acid A in addressing RIT.