Miracle-dz/UniFAR-FTUs huggingface dataset:
The permissive binding theory of cancer

The later stages of cancer, including the invasion and colonization of new tissues, are actively mysterious compared to earlier stages like primary tumor formation. While we lack many details about both, we do have an apparently successful explanatory framework for the earlier stages: one in which genetic mutations hold ultimate causal and explanatory power. By contrast, on both empirical and conceptual grounds, it is not currently clear that mutations alone can explain the later stages of cancer. Can a different type of molecular change do better? Here, I introduce the “permissive binding theory” of cancer, which proposes that novel protein binding interactions are the key causal and explanatory entity in invasion and metastasis. It posits that binding is more abundant at baseline than we observe because it is restricted in normal physiology; that any large perturbation to physiological state revives this baseline abundance, unleashing many new binding interactions; and that a subset of these cause the cellular functions at the heart of oncogenesis, especially invasion and metastasis. Significant physiological perturbations occur in cancer cells in very early stages, and generally become more extreme with progression, providing interactions that continually fuel invasion and metastasis. The theory is compatible with, but not limited to, causal roles for the diverse molecular changes observed in cancer (e.g. gene expression or epigenetic changes), as these generally act causally upstream of proteins, and so may exert their effects by changing the protein binding interactions that occur in the cell. This admits the possibility that molecular changes that appear quite different may actually converge in creating the same few protein complexes, simplifying our picture of invasion and metastasis. If correct, the theory offers a concrete therapeutic strategy: targeting the key novel complexes. The theory is straightforwardly testable by large-scale identification of protein interactions in different cancers.
Quantum Mode Series Resonant Converter Utilized as Active Voltage Regulator of a Split DC Bus Capacitor

Certain modern power electronics systems require active regulation of the split DC bus capacitor voltages. The series resonant converter is suitable to be utilized as an active voltage regulator, due to its ability to operate with soft switching, and hence, with high efficiency. In discontinuous conduction mode, the series resonant converter operates with a constant unity voltage gain, thus achieving balancing of the DC link. However, discontinuous conduction mode does not provide means for achieving a different voltage distribution, which is important in many scenarios. On the other hand, by operating in quantum mode (i.e. type 2 discontinuous conduction mode), the voltages across DC bus capacitor can be regulated. Therefore, the modeling of the quantum mode series resonant converter connected across split DC bus is presented in this paper. The steady-state operation as well as transient behavior are discussed and experimentally verified on a laboratory prototype.
Fine mapping of qBK1.2, a major QTL governing resistance to bakanae disease in rice

Bakanae disease caused by Fusarium fujikuroi is an emerging disease of rice causing losses in all rice-growing regions around the world. A BC2F2 population was developed by backcrossing the recurrent parent Pusa Basmati 1121 (PB1121) with the recombinant inbred line RIL28, which harbors a major quantitative trait locus (QTL) governing resistance to bakanae, qBK1.2. MassARRAY-based single-nucleotide polymorphism (SNP) assays targeting the genomic region of qBK1.2 helped in fine mapping the QTL to a region of 130 kb between the SNP markers rs3164311 and rs3295562 using 24 recombinants. In-silico mining of the fine-mapped region identified 11 putative candidate genes with functions related to defense. The expression analysis identified two significantly differentially expressed genes, that is, LOC_Os01g06750 and LOC_Os01g06870, between the susceptible genotype PB1121 and the resistant genotypes Pusa1342 and R-NIL4. Furthermore, the SNPs identified in LOC_Os01g06750 produced minor substitutions of amino acids with no major effect on the resistance-related functional motifs. However, LOC_Os01g06870 had 21 amino acid substitutions, which led to the creation of the leucine-rich repeat (LRR) domain in the resistant genotype Pusa1342, thereby making it a potential candidate underlying the major bakanae-resistant QTL qBK1.2. The markers used in the fine mapping program are of immense utility in marker-assisted breeding for bakanae resistance in rice.
Dancing in a Tutu: Using a Ballet Robot to Encourage Young Girls into Robotics

Despite recent initiatives, the number of women in programming and software engineering has continued to drop over recent years. One potential reason for this drop is that girls “learn” early on that programming is a boys’ activity and that they are not good at it. Therefore, they are less likely to choose topics relating to programming as they progress through their studies. Thus, one approach to increasing women in programming is to target girls at an early age and show them that programming is both doable and fun. This paper presents a pilot study involving a robotic programming system for girls aged five to ten. The children used a tangible-based programming system to program ballet dances on a Nao robot in a real-world classroom. The results indicate that the participants enjoyed the system and could build programs without many issues. While this study only includes a small data set, it does validate the overall idea and suggests that further research in the area is beneficial.
C-NARS/P: An Open-Source Tool for Classification of Narratives in Survey Data Using Pre-Trained Language Models

This report presents an open-source tool (C-NARS/P) created to classify narratives in survey data using pre-trained language models. Unlike conventional machine learning methods, pre-trained language models such as BERT can utilize context of words in text to make accurate predictions. In this report, technical details of functions and parameter setups for implementing pre-trained language models for classification are provided with screenshots of the code file to guide users for validation and improvement of the implementation. C-NARS/P can be modified for a wide range of text classification tasks with ease
A multisensory mindfulness experience: exploring the promotion of sensory awareness as a mindfulness practice

Objectives In this preliminary and multidisciplinary exploratory study, we assessed whether a mindfulness practice could be enhanced through a multisensory experience design that mimics the “beginner’s mind,” relying on sensory awareness and biofeedback processes as participants interact with the experience. Methods We piloted and designed two conditions, being (a) a guided mindfulness practice based on the senses as an anchor to the present moment, using audio instruction only; and (b) an experience of mindfulness practice with successive sensory stimulation (olfactory, audio, and visual stimulation) followed by an interactive experience with biofeedback that provides a visual representation of the person’s heartbeat in real-time. For each of the conditions we assessed anxiety (state and trait), as well as other psychological variables pre- and post-experience. Additionally, we measured the heart rate variability (HRV) at baseline, during each stage of the experience as well as post intervention. Results We collected valid data for a total of 68 individuals. Both groups were similar regarding mean age, sex, and occupation and had similar prior experience with mindfulness. There were no significant differences regarding prior state or trait anxiety between the groups. Analysis of the physiological variables showed that for both groups there was an increase in the parasympathetic activity after the multisensory experience, with small differences in the conditions of stimulation. We did not observe significant differences between the pre and post measures for state of test anxiety. The observed parasympathetic activity variations after both experiences compared with pre and post-surveys demonstrate the importance of physiological vs psychological inspection beyond the common human rational experience that is not always resonate with the body’s response and impacts the needed literacy to self-awareness of emotional well-being. Conclusion Participants in both conditions could effectively connect with the experience, while achieving a physiological response different from their baseline state. The acceptance of the designed stimuli was very high, although more research is still needed to uncover its full potential. In sum, the design of multisensory experiences using technology to create an interactive connection with the sensory stimulus, is a promising field in mindfulness and especially in practices involving sensory awareness through the monitoring of parasympathetic activity as an inference indicator of the present-moment connection.
Developing a Comprehensive Approach to Climate Change Policy in the United States: Integrating Levels of Government and Economic Sectors

The United State Supreme Court's holding in Massachusetts v. EPA that greenhouse gases are air pollutants under the Clean Air Act makes it virtually certain that federal climate change legislation will be accomplished by amending that Act. This Article explains and justifies an approach to federal climate legislation that uses and builds on the Act's various tools, including air quality standards, technology-based limitations, and state implementation plans. The Article discusses models for climate response that have emerged from state responses to date and presents the reductions that could be achieved if these were scaled up to the federal level. Federal legislative proposals to date fail to build upon these state lessons and do not provide adequate mechanisms to support the multi-faceted economy wide approach that can achieve needed reductions in a cost-effective manner. We suggest a mechanism whereby the Clean Air Act could be applied or adapted to incorporate state creativity to support the integrated, economy-wide approach that is needed. This approach could also motivate both the individual action and the international cooperation that are required to address climate change effectively.
Classification of Arecanut X-Ray Images for Quality Assessment Using Adaptive Genetic Algorithm and Deep Learning

The traditional approach for analyzing the quality of arecanuts is based on their external appearance. However, using machine learning and deep learning techniques, automated classifications were performed. But the true quality can only be analyzed when the internal structure of the arecanut is examined. Therefore, we use the X-ray imaging technique to determine the internal quality of arecanuts. We prepared a novel dataset of arecanut X-ray images and used a YOLOv5 based deep learning architecture for classification. The present study employs an adaptive genetic algorithm based approach for hyperparameter optimization to enhance the mean average precision (mAP) using a light weight model generated using a ghost network and a feature pyramid network (FPN). We have achieved the highest mAP of 97.84% using our method with a lower model size of 15 MB. Our method has excelled in detecting the arecanut compared to cutting-edge object detection algorithms such as YOLOv3, YOLOv4, Detetron, YOLOv6, YOLOv8, and YOLOX. We also acknowledged the performance enhancement using the adaptive genetic algorithm on the Pascal VOC 2007 image dataset. Despite of significant computational requirements for executing genetic algorithms, we proved that genetic algorithms can boost mAP. Additionally, the methodology developed in this investigation produced multiple models with the best mAP featuring optimized hyperparameters. This methodical strategy is helpful for the design of an automatic, non-destructive, integrated X-ray image based classification system. This system has the potential to revolutionize the quality assessment of arecanuts by offering a more efficient evaluation method.
Soil losses in rainfed Mediterranean vineyards under climate change scenarios. The effects of drainage terraces.

Most vines in the Mediterranean are cultivated on bare soils, due to the scarcity of water. In addition, most traditional soil conservation measures have been eliminated to facilitate the movement of machinery in the fields. In such conditions, high erosion rates are recorded. Given the predicted changes in precipitation and an increasing number of extreme events, an increase in erosion processes is expected. In this study, erosion processes under different climate change scenarios were evaluated as well as the effects of implementing drainage terraces in vineyards. Soil losses were simulated using the WEPP model. The results confirmed the relevance of extreme events on annual soil losses. The WEPP model gave satisfactory results in predicting runoff and soil losses, although the soil losses recorded after some extreme events were under-predicted. The model responded to changes in precipitation and because of that a decrease in precipitation gave rise to a decrease in soil losses. For the scenario in 2050, runoff volumes decreased between 19.1 and 50.1%, while erosion rates decreased between 34 and 56%. However, the expected increase in rainfall intensity may contribute to higher erosion rates than at present. The construction of drainage terraces, perpendicular to the maximum slope, 3 m wide and 30 m between terraces, may lead to an average decrease in soil losses of about 45%.
Measures of social segregation in the context of Warsaw, Berlin and Paris metropolitan areas

Abstract Social segregation is a subject common in contemporary studies of metropolitan areas. Until recently, studies of segregation focused on the distribution of ethnic groups, immigrants, and the poor. Today, they also cover additional indicators such as demographic properties, education, and affiliation with social and professional categories, which can also serve to determine the causes of the segregation (including the self-segregation of the rich). This article aims to point out the measures of segregation that present the segregation levels in the most complete manner, along with their application in the context of three European metropolitan areas: Warsaw, Berlin, and Paris. The first part of the article is a review of the existing approaches to segregation measures, followed by the selection of research method, presentation of the analysis’ results, and evaluation of the applied methods; presenting the opportunities and limitations in research of the social segregation phenomenon.
Cognitive Screening and Hearing Assessment in Patients With Chronic Tinnitus

Objectives. The study aimed to assess the relationship of tinnitus with hyperacusis with cognitive impairment as indicated by the Montreal Cognitive Assessment (MoCA) tool. Methods. This multicenter cross-sectional study included individuals with chronic tinnitus from the “Unification of Treatments and Interventions for Tinnitus Patients” (UNITI) database. Participants were recruited from four different tertiary clinical centers located in Athens and Granada (Mediterranean group), as well as Berlin and Regensburg (German group). In total, 380 individuals with a diagnosis of non-pulsatile chronic tinnitus (permanent and constant tinnitus lasting more than 6 months) and no evidence of severe cognitive impairment (MoCA score >22) were enrolled. The evaluation utilized the following tools: MoCA, Tinnitus Handicap Inventory (THI), Hyperacusis Questionnaire (GÜF), Patient Health Questionnaire (PHQ-9), and the European School for Interdisciplinary Tinnitus Research Screening Questionnaire. Results. MoCA scores differed between German and Mediterranean individuals (P<0.01), necessitating separate analyses for each group. In both cohorts, MoCA scores were significantly associated with education level, age, hearing threshold at 8 kHz, and THI. Furthermore, a significant correlation was observed between PHQ-9 scores and both THI and GÜF (P<0.01 for both Germans and those from the Mediterranean). Conclusion. Our data suggest an association between tinnitus handicap, high-frequency hearing loss, and mild cognitive impairment. Additionally, PHQ-9 scores were associated with tinnitus and hyperacusis scores, independent of hearing loss thresholds.
Fast Designing Ladder Diagram of Programmable Logic Controller for a Technological Process

— The article presents developed method and general principles of creating ladder diagrams, which are commonly used for systems with programmable logic controllers (PLC). Ladder diagrams are created for sequential control systems of technological processes, which are described by a connection pattern, time diagrams of the executive elements` operation. The executive elements are double-acting pneumatic or hydraulic actuators controlled by bistable electrovalves. A method of designing sequential systems enabling the creation of a ladder electro-pneumatic system is presented. The ladder diagram consists of two parts. One is responsible for controlling the valve coils, the other for the implementation of the memory block. The signals that control the transition to the next state are the signals described on the boundaries of the graph division. The synthesis of control systems and their verification was carried out using the computer aided program FluidSim by Festo.
Detection of Various Dental Conditions on Dental Panoramic Radiography Using Faster R-CNN

The dental panoramic radiograph (DPR) is a pivotal diagnostic tool in dentistry. However, despite the growing prevalence of artificial intelligence (AI) across various medical domains, manual methods remain the prevailing means of interpreting DPR images. This study aims to introduce an advanced identification system for detecting seven dental conditions in DPR images by utilizing Faster R-CNN. The primary objectives are to enhance dentists’ efficiency and evaluate the performance of various CNN models as foundational training networks. This study contributes significantly to the field in several notable ways. Firstly, including a Butterworth filter in the training process yielded an approximately 7% enhancement in judgment accuracy. Secondly, the proposed enhancement technology tailored to different dental symptoms effectively bolstered the training model’s accuracy. Consequently, all dental conditions attained an accuracy rate exceeding 95% in CNN analysis. These accuracy enhancements ranged from 1.34% to 13.24% compared to existing recognition technologies. Thirdly, this study pioneers the application of Faster R-CNN for identifying dental conditions, achieving an impressive accuracy rate of 94.18%. The outcomes of this study mark a substantial advancement compared to prior research and offer dentists a more efficient and convenient means of pre-diagnosing dental conditions.
Living with Haru4Kids: Study on children’s activity and engagement in a family-robot cohabitation scenario

Haru4Kids (H4K) is a system that emulates the physical, social, family-oriented robot Haru, designed with the goal to cohabitate with children in their home for extended periods of time. Seven families kept H4K for two net weeks in their homes. Throughout this period of cohabitation, we collected user logs comprised of the children users ’ head angles, the rotation angles of the platform, and the actions taken by H4K as well as captured images which were afterwards hand-annotated to estimate user engagement. We report the trends of these external metrics that we collected during every session of interaction. We also developed an annotation tool and report the Engagement Level Metric we chose to estimate child engagement throughout interactions “in-the-wild. ” Overall, our platform offers a feasible system that can engage with children while also allowing us to monitor their engagement and behaviour throughout each interaction.
Numerical study of subgrade humidity field evolution with different compaction models

To study the subgrade humidity field distribution with different compaction models, 4 subgrade numerical models with different compaction conditions were established. Through analyzing tow-dimensional infiltration rainfall test results, the influences of different compaction models on the humidity disturbed zone distributions, the extended distances, the subgrade humidity values and gradients were examined. The mechanisms behind these findings were explained. The results show that humidity disturbed zone appears after rainfall infiltration and it can be divided into front and back zone. The characteristics of back zone include the larger humidity and the smaller gradient,while the front zone just has the opposite conditions. The extended distances and humidity values of the disturbed zone decrease linearly with the increase of subgrade compaction degree. The humidity gradient of the front zone increases linearly with the increase of subgrade compaction degree. Since the vertical component of the rainfall infiltrating velocity vector is considerably larger than the horizontal one, the subgrade humidity of a deep layer decreases significantly with the increase of upper subgrade compaction in unsaturated disturbed zones, which is also affected by the composition of subgrade compaction zones.
Solvent-Free Synthesis of Multifunctional Block Copolymer and Formation of DNA and Drug Nanocarriers

The synthesis of well-defined multifunctional polymers is of great importance for the development of complex materials for biomedical applications. In the current work, novel and multi-amino-functional diblock copolymer for potential gene and drug delivery applications was successfully synthesized. A highly efficient one-step and quantitative modification of an alkyne-functional polycarbonate-based precursor was performed, yielding double hydrophilic block copolymer with densely grafted primary amine side groups. The obtained positively charged block copolymer co-associated with DNA, forming stable and biocompatible nanosized polyplexes. Furthermore, polyion complex (PIC) micelles with tunable surface charge and decorated with cell targeting moieties were obtained as a result of direct mixing in aqueous media of the multi-amino-functional block copolymer and a previously synthesized oppositely charged block copolymer bearing disaccharide end-group. The obtained well-defined nanosized PIC–micelles were loaded with the hydrophobic drug curcumin. Both types of nanoaggregates (polyplexes and PIC–micelles) were physico-chemically characterized. Moreover, initial in vitro evaluations were performed to assess the nanocarriers’ potential for biomedical applications.
Thermomechanical Response of Geothermal Energy Pile Groups in Sand

AbstractThe thermomechanical response of geothermal energy pile groups in sand was studied in the present work by using a three-dimensional nonlinear finite-element analysis procedure. A raft was considered on the piles. The stress-strain responses of the piles and raft were considered linear elastic. The stress-strain response of sand was reproduced by using the state parameter-based constitutive clay and sand model (CASM). The CASM was implemented in finite-element software through a user-defined material subroutine. The geothermal energy pile group was analyzed for different combinations of thermal and nonthermal piles in the group in a single layer of sand. Analysis results were studied for the displacement at the base of the pile and the axial stresses in the pile. Parametric sensitivity studies were performed by varying the spacing between the piles. It can be observed from the results that the geothermal piles, when subjected to heating, exhibit higher displacement and axial stress than the piles u.