Miracle-dz/UniFAR-FTUs huggingface dataset:
Immune Effective Score as a Predictor of Response to Neoadjuvant Trastuzumab Therapy and a Prognostic Indicator for HER2-Positive Breast Cancer

Background: HER2-positive breast cancer (BC) is a highly aggressive phenotype. The role of the host immune features in predictive response to anti-HER2 therapies and prognosis in BC has already been suggested. We aimed to develop a predictive and prognostic model and examine its relevance to the clinical outcomes of patients with HER2-positive BC. Methods: Immune effective score (IES) was constructed using principal component analysis algorithms. A bioinformatic analysis using four independent cohorts (GSE66305, n = 88; GSE130786, n = 110; TCGA, n = 123; METABRIC, n = 236) established associations between IES and clinical outcomes. Results: Genes associated with neoadjuvant trastuzumab therapy response were enriched in pathways related to antitumor immune activities. IES was demonstrated to be a predictive biomarker to neoadjuvant trastuzumab therapy benefits (GSE66305: area under the curve (AUC) = 0.804; GSE130786: AUC = 0.704). In addition, IES was identified as an independent prognostic factor for overall survival (OS) in the TCGA cohort (p = 0.036, hazard ratio (HR): 0.66, 95% confidence interval (CI): 0.449–0.97) and METABRIC cohort (p = 0.037, HR: 0.9, 95% CI: 0.81–0.99). Conclusion: IES has a predictive value for response to neoadjuvant trastuzumab therapy and independent prognostic value for HER2-positive breast cancer.
Social enterprises and regional cities: working together for mutual benefit

ABSTRACT Social enterprises respond to local needs through an integrated economic and social model. It is known that social enterprises facilitate outcomes for their participants; less is known about how social enterprises contribute to outcomes for others in their locale. Activity within social enterprises was observed and interviews conducted with participants, staff, customers and leaders in Australian regional cities. Data were analysed using a conceptual framework informed by social capital and social enterprise literature that uncovered actions involving social enterprises that realise place-based outcomes, motivations for these actions, and social capital networks that facilitate them. Linking networks among high level actors in regional cities supported development of bridging networks between social enterprises and other organisations. These were activated by social enterprises or others to generate opportunities for social enterprise participants. Local organisation motivations for interacting with social enterprises complemented social enterprises’ dual social and economic mission. Local production and ‘consumption’ of products realised benefits including wellbeing and social inclusion. Findings extend knowledge by showing that social enterprises’ dual social and economic missions place them in multiple networks with overlapping membership. Network overlap generates a space for work on place-based social and economic problems and opportunities that benefit social enterprises and cities.
A novel linear matrix inequality‐based robust event‐triggered model predictive control for a class of discrete‐time linear
 systems

This paper studies a linear matrix inequality (LMI)‐based robust event‐triggered model predictive control (ET‐MPC) for a class of discrete linear time‐invariant systems subject to bounded disturbances. In the presented robust event‐triggered MPC, the event‐triggered mechanism is first set by the deviation between the optimal state and actual state. In addition, the Lyapunov‐based stability condition is employed in the constraints for simplifying parameters and enhancing the universality. Subsequently, a novel design framework that involves LMIs approach is developed. In such a framework, the Lyapunov weight matrix is predesigned by solving a convex optimization problem with LMIs and the infinite horizon MPC optimization problem is also transformed as LMIs such that the computational complexity is significantly reduced. To guarantee robust constraint satisfaction, a dual‐mode control strategy is adopted. In this way, the proposed robust ET‐MPC has the ability to deal with the constrained system. Furthermore, the theoretical analysis of the recursive feasibility and stability is provided. The numerical simulations and comparison studies demonstrate that the proposed robust ET‐MPC not only has satisfying control performance but also significantly reduces the computational burden.
Development and Characterization of Anti-alzheimer Drug-loaded Chitosan Nanoparticles for the Enhanced Penetration of Blood Brain Barrier

Nanotechnology facilitated drug delivery has been used to enhance the drug bioavailability, efficacy, reduce toxicity and improve patient compliance aiming to targetthe cells and tissues to produce anticipated pharmacological action. The aim of the present study was to formulate and evaluate rivastigmine (RT) loaded chitosan (CS) nanoparticles for sustained release. RT is a short actingreversible acetylcholinesterase inhibitor used for the treatment of mild to moderate Alzheimer's and Parkinson's disease. In current research RT loaded CS-tripolyphosphate (TPP) nanoparticles were prepared by usingionic gelation method in fourdifferent polymer concentrations (0.1%,0.2%,0.3%,0.4%). The prepared nanoparticles were evaluated by Zeta sizer in order to determine particle size, PDI and zeta potential. Further, drug entrapment efficiency and in vitro release studies were carried out. The results showed that particle size decreased by loading drug within nanoparticles when compared with unloaded nanoparticles. The particle size of RT loaded CS nanoparticles ranged from 125.9 ± 2.5 to 356.0 ± 7.9 by varying CS concentration from 0.1% to 0.4% w/v. Among different ratios studied, 0.4% ratio showed highest drug entrapment efficiency (80%). In vitro release studies showed that RT loaded CS nanoparticles could sustain release the drug.In conclusion, the current research results showed that the chitosan nanoparticles can be used as a potential carrier for providing sustained delivery of RT.
Classification and Grip of Occluded Objects

The present paper exposes a system for detection, classification, and grip of occluded objects by machine vision, artificial intelligence, and an anthropomorphic robot, to generate a solution for the subjection of elements that present occlusions. The deep learning algorithm used is based on Convolutional Neural Networks (CNN), specifically Fast R-CNN (Fast Region-Based CNN) and DAG-CNN (Directed Acyclic Graph CNN) for pattern recognition, the three-dimensional information of the environment was collected through Kinect V1, and tests simulations by the tool VRML. A sequence of detection, classification, and grip was programmed to determine which elements present occlusions and which type of tool generates the occlusion. According to the user's requirements, the desired elements are delivered (occluded or not), and the unwanted elements are removed. It was possible to develop a program with 88.89% accuracy in gripping and delivering occluded objects using networks Fast R-CNN and DAG-CNN with achieving of 70.9% and 96.2% accuracy respectively, detecting elements without occlusions for the first net and classifying the objects into five tools (Scalpel, Scissor, Screwdriver, Spanner, and Pliers), with the second net. The grip of occluded objects requires accurate detection of the element located at the top of the pile of objects to remove it without affecting the rest of the environment. Additionally, the detection process requires that a part of the occluded tool be visible to determine the existence of occlusions in the stack
Thirty years with Flora Croatica database

The Flora Croatica (FCD) database records thirty years of continuous work these days. Since the initial limited application, today FCD has been nationally and internationally recognized as the relevant source of verified data on national and regional flora. It is fully web oriented with the strong support of GIS tools in spatial data display and analysis. Users are a wide range of individuals, public institutions, museums, educational system institutions, scientific institutions, and private companies. With numerous interconnected modules, it enables the processing and presentation of various data on flora – taxonomy, nomenclature, distribution, threat status, use, invasiveness, bibliography, collections, etc. Website monitoring indicates great dynamics of data entry, processing, and use, as well as international cooperation. Further development of FCD and application of modern IT tools in the best possible support to all classes of users is expected, both in quantitative and qualitative terms.
Korean laryngeal contrast revisited: An electroglottographic study on denasalized and oral stops

In several Korean dialects, domain-initial nasal onsets undergo denasalization as a recent sound change. Nasal stops may be realized as prevoiced or even devoiced stops. This makes it necessary to examine the interplay of phonetic properties of the denasalized and the three oral stop series as a whole, in synchrony and diachrony. What are their concomitant and conflicting properties? Our study provides a bigger picture of the laryngeal contrast in Seoul and Gyeonggi Korean by examining the acoustic distributions related to the laryngeal properties of the four stop series, using acoustic and electroglottographic data. VOT and f0 play important roles in the distinction of the four stop series, in line with previous studies. While the contribution of voice quality is relatively minor, we show that it plays an essential role of disambiguation when the VOT–f0 space gets crowded: When lenis stops can be confused with other stops, there is an enhancement of breathy voice. Finally, we discuss stop variation according to prosodic contexts. We highlight the basis of both syntagmatic variation and paradigmatic contrast in their phonetic implementations. They illustrate a constant reorganization to reconcile contrast maintenance with constraints from articulatory and perceptual systems, as well as language-specific structures.
A Novel Model Using Virtual State Variables and Bayesian Discriminant Analysis to Classify Surrounding Rock Stability

To accurately classify the stability of surrounding rock masses, a novel method (VSV-BDA) based on virtual state variables (VSVs) and Bayesian discriminant analysis (BDA) is proposed. The factors influencing stability are mapped by an artificial neural network (ANN) capable of recognizing the model of rock mass classification, and the obtained output vector is treated as VSVs, which are verified as obeying a multinormal distribution with equal covariance matrixes by normal distribution testing and constructed statistics. The prediction variance ratio test method is introduced to determine the optimal dimension of the VSVs. The VSV-BDA model is constructed through the use of VSVs and the optimal dimension on the basis of the training samples, which are divided from the collected samples into three situations having different numbers. ANN and BDA models are also constructed based on the same training samples. The predictions by the three models for the testing samples are compared; the results show that the proposed VSV-BDA model has high prediction accuracy and can be applied in practical engineering.
Microbial Community Composition Correlates with Metal Sorption in an Ombrotrophic Boreal Bog: Implications for Radionuclide Retention

Microbial communities throughout the 6.5 m depth profile of a boreal ombrotrophic bog were characterized using amplicon sequencing of archaeal, fungal, and bacterial marker genes. Microbial populations and their relationship to oxic and anoxic batch sorption of radionuclides (using radioactive tracers of I, Se, Cs, Ni, and Ag) and the prevailing metal concentrations in the natural bog was investigated. The majority of the detected archaea belonged to the Crenarchaeota, Halobacterota, and Thermoplasmatota, whereas the fungal communities consisted of Ascomycota, Basidiomycota, and unclassified fungi. The bacterial communities consisted mostly of Acidobacteriota, Proteobacteria, and Chloroflexi. The occurrence of several microbial genera were found to statistically significantly correlate with metal concentrations as well as with Se, Cs, I, and Ag batch sorption data. We suggest that the metal concentrations of peat, gyttja, and clay layers affect the composition of the microbial populations in these nutrient-low conditions and that particularly parts of the bacterial and archaeal communities tolerate high concentrations of potentially toxic metals and may concurrently contribute to the total retention of metals and radionuclides in this ombrotrophic environment. In addition, the varying metal concentrations together with chemical, mineralogical, and physical factors may contribute to the shape of the total archaeal and bacterial populations and most probably shifts the populations for more metal resistant genera.
Modeling and Prediction of Land Use Land Cover Change Dynamics Based on Land Change Modeler (LCM) in Nashe Watershed, Upper Blue Nile Basin, Ethiopia

Change of land use land cover (LULC) has been known globally as an essential driver of environmental change. Assessment of LULC change is the most precise method to comprehend the past land use, types of changes to be estimated, the forces and developments behind the changes. The aim of the study was to assess the temporal and spatial LULC dynamics of the past and to predict the future using Landsat images and LCM (Land Change Modeler) by considering the drivers of LULC dynamics. The research was conducted in Nashe watershed (Ethiopia) which is the main tributary of the Upper Blue Nile basin. The total watershed area is 94,578 ha. The Landsat imagery from 2019, 2005, and 1990 was used for evaluating and predicting the spatiotemporal distributions of LULC changes. The future LULC image prediction has been generated depending on the historical trends of LULC changes for the years 2035 and 2050. LCM integrated in TerrSet Geospatial Monitoring and Modeling System assimilated with MLP and CA-Markov chain have been used for monitoring, assessment of change, and future projections. Markov chain was used to generate transition probability matrices between LULC classes and cellular automata were used to predict the LULC map. Validation of the predicted LULC map of 2019 was conducted successfully with the actual LULC map. The validation accuracy was determined using the Kappa statistics and agreement/disagreement marks. The results of the historical LULC depicted that forest land, grass land, and range land are the most affected types of land use. The agricultural land in 1990 was 41,587.21 ha which increased to 57,868.95 ha in 2019 with an average growth rate of 39.15%. The forest land, range land, and grass land declined annually with rates of 48.38%, 19.58%, and 26.23%, respectively. The predicted LULC map shows that the forest cover will further degrade from 16.94% in 2019 to 8.07% in 2050, while agricultural land would be expanded to 69,021.20 ha and 69,264.44 ha in 2035 and 2050 from 57,868.95 ha in 2019. The findings of this investigation indicate an expected rapid change in LULC for the coming years. Converting the forest area, range land, and grass land into other land uses, especially to agricultural land, is the main LULC change in the future. Measures should be implemented to achieve rational use of agricultural land and the forest conversion needs to be well managed.
What's in a name? Challenging the commodification of pollination through the diverse economies of 'Bee Cities'

One million species are threatened with extinction globally,including more than half of the native bee species in North America. In Canada,as of July 2020, 42 municipalities have signed a resolution to commit to the standards of the Bee City Canada program which includes creating and enhancing pollinator habitat, along with celebrating and raising awareness about pollinators in their communities. Our central argument is that the commodification of pollination has detrimental effects on people, pollinators,and ecosystems, and that a diverse economies framework is one conceptual model that can help shift our perspective. Within the 'save the bees' narrative, a capitalocentric, unidimensional image of pollination persists, driven by particular forms of market power and domination. Well-intentioned individuals and groups may be constrained by industry-dominated messaging that limits their understanding of appropriate interventions. Meanwhile, Bee City Canada offers municipalities the opportunity to engage in conservation efforts by starting where they are and building on a network of Bee Cities across the country. We conducted a collective case study involving in-depth interviews with members of Ontario Bee Cities. Our thematic interpretive analysis shows how a diverse economies framework can help us to understand the value and contributions of this initiative in previously undervalued and under-recognized ways and how they help to advance a whole-of-community approach. It is only through decentering the hegemonic market-based view of pollination that true conservation of bee diversity, and associated pollination services, can be prioritized. Our findings show that Bee Cities can animate a vibrant political ecology through a collective municipal identity, by centering bees (and other pollinators by proxy.
Cultivating Nature Identity and Ecological Worldviews: A Pathway to Alter the Prevailing Dominant Social Paradigm

The worsening environmental problems demand a shift from the prevailing Dominant Social Paradigm to the New Ecological Paradigm. Yet, little is known on the conditions necessary for societal adoption of conservation behaviour. This qualitative study explores the social-psychological aspects and processes cultivating ecological identity and worldviews by uncovering the activities, interpretation of experiences that capture mental thoughts, emotions and symbolic meanings within the richness of lived experiences. The findings theorise the process of ecological identity building and offers in-depth insights into the motivations and stages of ecological identities and worldviews that support pro-environmental behaviour. The insights extend the identity theory to illustrate the process of nature identity development to include the stages of identity activation, creation and synthesis; reveal Asian values and beliefs that consumers use to rationalise their consumption behaviour; and provide implications for macromarketing, education and sustainability initiatives, and policy making.
FORMULATION AND EVALUATION OF SOLID DISPERSION TABLETS OF FUROSEMIDE USING POLYVINYLPYRROLIDONE K-30

Objective: The objective of the present study was to improve the aqueous solubility and dissolution characteristics of the loop diuretic furosemide (FUR); a class IV drug in the Biopharmaceutical Classification System (BCS) using solid dispersion technique. Methods: Solvent evaporation and kneading methods were used to produce solid dispersions of FUR in different ratios with the hydrophilic carrier polyvinylpyrrolidone K-30 (PVP-K30). The prepared solid dispersions were evaluated in terms of solubility study, percentage yield, drug content and Fourier transform infrared spectroscopic study (FT-IR). Tablets containing the optimized formula of solid dispersions ( were formulated and their dissolution characteristics were compared with commercial furosemide tablets. Results: The prepared solid dispersions showed an increase in aqueous solubility, especially those formulated in a 1:2 drug: carrier ratio using solvent evaporation method ( it showed a four-fold increase in solubility compared to the parent drug. The absence of drug-carrier chemical interactions that could affect the dissolution was proved by FT-IR. Solid dispersion tablets exhibited a better dissolution profile in simulated gastric fluid pH 1.2 at 37°C ± 0.5 than the commercial FUR tablets in terms of mean dissolution time (8.44 min) and dissolution efficiency in 30 min (42.54%). Both FUR solid dispersions and commercial tablets followed Weibull and Krosmeyer models as the two best models of drug release kinetics proving that they were immediate release. Conclusion: According to the results obtained in this study, solid dispersion techniques could be successfully used for the enhancement of aqueous solubility and dissolution rate of FUR.
Firefly Algorithm-Based Photovoltaic Array Reconfiguration for Maximum Power Extraction during Mismatch Conditions

This studyaimed at improving the performance and efficiency of conventional static photovoltaic (PV) systems by introducing a metaheuristic algorithm-based approach that involves reconfiguring electrical wiring using switches under different shading profiles. Themetaheuristicalgorithmused wasthe firefly algorithm (FA), which controls the switching patterns under non-homogenous shading profiles and tracks the highest global peak of power produced by the numerous switching patterns. This study aimed to solve the current problems faced by static PV systems, such as unequal dispersion of shading affecting solar panels, multiple peaks, and hot spot phenomena, which can contribute to significant power loss and efficiency reduction. The experimental setup focusedon software development and the system or model developed in the MATLAB Simulink platform. Athorough and comprehensive analysis was done by comparing the proposed method’s overall performance and power generation with thenovel static PVseries–parallel (SP) topology and totalcross-tied (TCT) scheme. The SP configuration is widely used in the PV industry. However, the TCT configuration has superior performance and energy yield generation compared to other static PV configurations, such as the bridge-linked (BL) and honey comb (HC) configurations. The results presented in this paper provide valuable information about the proposed method’s features with regard toenhancing the overall performance and efficiency of PV arrays.
Stability of Coal Pillar and Roof Movement Characteristics in Roadway Backfill Mining

In order to explore the stability of coal pillar and the characteristics of roof movement during the process of roadway backfill mining (RBM), the 301 backfilling test working face of Ordos Chahasu coal mine is taken as the background. Based on the expansive pressure arch theory, the evolution process of the stope expansive pressure arch in RBM is studied; by establishing a mechanical model for the stability of coal pillars, the interactions between the height, width, and the maximum number of branches are obtained. When the width and height of the branch are both 5 m, the optimal number of the branches is obtained. Then, by establishing a mechanical model for the subsidence of the immediate roof, the process of the immediate roof subsidence is divided into three stages, namely, the formation stage of the local pressure arch, the merge stage of the pressure arch, and the expansion stage of the pressure arch. In addition, using the numerical method, the alternate bearing process of coal pillars and filling bodies and the change of the maximum supporting stress are studied, and the evolution of the pressure arch bearing structure above the stope and the staged subsidence characteristics of the roof are analyzed. The on-site test showed that the coal pillar has a good stability during the mining process. The maximum stress of the coal pillar is 16.5 MPa, and the maximum stress of the filling body is 9 MPa. The maximum settlement of the immediate roof is 102 mm, indicating that the roof control effect is good. This research will play an important role on engineering practice.