Miracle-dz/UniFAR-FTUs huggingface dataset:
Establishment and Validation of a Predictive Nomogram for Postoperative Survival of Stage I Non-Small Cell Lung Cancer

Background Surgical procedure is the preferred option for people with early-stage non-small cell lung cancer (NSCLC), while nearly 30% of patients experienced metastatic or recurrent tumor after operation. The primary intention of this context is to summarize high-risk prognostic factors and set up a novel nomogram to predict the overall survival of individuals with stage I NSCLC after resection. Methods Research objects, 10,218 patients with stage I NSCLC after operation from 2010 to 2015, were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Independent prognostic factors, confirmed by Cox regression analyses, were integrated into a nomogram, to predict the 3-and 5-year overall survival of these individuals. The model experienced internal validation of testing cohorts above and external validation crewed by 160 patients from China. Finally, the nomogram was evaluated through several verification methods such as concordance index (C-index), calibration plots and receiver operating characteristic curve (ROC). Results Multivariate analysis identified that age, gender, histologic type, differentiation class, type of operation, T stage and treatment were significant predictive factors for the survival of stage I NSCLC. Based on these factors, a nomogram was constructed to predict the 3- and 5-year overall survival of these individuals. Meanwhile, in the training set, this nomogram displayed excellent superiority over the TNM staging system with abroad application, especially in C-index (0.669 vs 0.580) and the AUC (the Area Under ROC Curve) for the 3- and 5-year survival (0.678 vs 0.582; 0.650 vs 0.576). In the calibration curve, the curve representing predicted survival tended to align with the line representing actual survival as well. Conclusion A nomogram was successfully created and verified to achieve the goal that made a rounded accurate prediction on the survival of postoperative I NSCLC patients in terms of the SEER database.
A Novel Differential to Single-Ended Converter for Ultra-Low-Voltage Inverter-Based OTAs

For the design of inverter-based OTAs with differential input and single-ended output, the differential to single-ended (D2S) converter is a key building block. In fact, the performance of the D2S strongly affects the overall common-mode rejection ratio (CMRR) and input common-mode range (ICMR) of the whole OTA. In recent literature, inverter-based OTAs rely on a D2S topology based on an inverter driving another inverter with the input and output tight together which behaves as a “diode” connected device to implement a voltage gain approximately equal to −1. However, since this approach is based on the matching of the inverters, the performance of this D2S results sensitive to PVT variations if the bias point of the inverters is not properly stabilized. In this paper we present a novel topology of inverter-based D2S converter, exploiting an auxiliary, standard-cell-based, error amplifier and a local feedback loop. The proposed D2S, compared to the conventional one, exhibits higher CMRR, improved ICMR and better robustness with respect to PVT variations. We present also an ULV, standard-cell-based OTA, which exploits the proposed D2S converter and shows excellent performance figures of merit with low area footprint.
Backpack: A Backpropagable Adversarial Embedding Scheme

A minmax protocol offers a general method to automatically optimize steganographic algorithm against a wide class of steganalytic detectors. The quality of the resulting steganograhic algorithm depends on the ability to find an “adversarial” stego image undetectable by a set of detectors while communicating a given message. Despite minmax protocol instantiated with ADV-EMB scheme leading to unexpectedly good results, we show it suffers a significant flaw and we present a theoretically sound solution called Backpack. Extensive experimental verification of minmax protocol with Backpack shows superior performance to ADV-EMB, the generality of the tool by targeting a new JPEG QF100 compatibility attack and further improves the security of steganographic algorithms.
Quantum Adiabatic Evolution Algorithms with Different Paths

In quantum adiabatic evolution algorithms, the quantum computer follows the ground state of a slowly varying Hamiltonian. The ground state of the initial Hamiltonian is easy to construct; the ground state of the final Hamiltonian encodes the solution of the computational problem. These algorithms have generally been studied in the case where the "straight line" path from initial to final Hamiltonian is taken. But there is no reason not to try paths involving terms that are not linear combinations of the initial and final Hamiltonians. We give several proposals for randomly generating new paths. Using one of these proposals, we convert an algorithmic failure into a success.
Ankle Inversion Proprioception Impairment in Persons with Chronic Ankle Instability Is Task-Specific

While investigators have often compared ankle proprioception between groups with and without chronic ankle instability (CAI), findings have been inconsistent. Possibly this is because ankle proprioceptive impairment in this population is task-specific. Thus, we aimed to compare ankle inversion proprioception in individuals with and without CAI in two task conditions: (i) when standing (not challenging) and (ii) when on a step-down landing (minimally-challenging). Ankle inversion proprioception was measured in both conditions for 38 recreational sport player volunteers with CAI (n = 19) and without CAI (n = 19). We used the Active Movement Extent Discrimination Apparatus (AMEDA) for the standing condition and the Ankle Inversion Discrimination Apparatus-Landing (AIDAL) for step-down landing. From analysis of variance (ANOVA) tests, CAI and non-CAI participants performed equally well on the AMEDA when standing; but the CAI group performed significantly worse than the non-CAI group on the AIDAL step-down landing task (p = 0.03). Within the non-CAI group, the AIDAL proprioceptive scores, as area under the receiver operating characteristics curve (AUC), were significantly higher than their AMEDA AUC scores (p = 0.03), while there was no significant difference between AIDAL and AMEDA AUC scores in the CAI group. Cumberland Ankle Instability Tool CAIT scores were significantly correlated with AIDAL scores (Spearman’s rho = 0.391, p = 0.015), but not with the AMEDA scores; and there was no significant correlation between the AIDAL and AMEDA scores. Thus, an ankle inversion proprioceptive deficit was evident for persons with CAI on the step-down AIDAL, and in a dose-response way, but not evident on the standing AMEDA, suggesting that ankle proprioceptive impairment is task-specific. Selected proprioceptive tests must present some minimal degree of challenge to the ankle joint in a functional task in order to differentiate CAI from non-CAI participants.
RESPONSES OF ONION PLANTS TO SOURCES AND RATES OF ORGANIC FERTILIZERS

Two field expermiments were carried out in which onion (Allium cepa) plants cv. Giza 20 were grown in clay soil supplied with different organic fertilizers i.e. poultry, sheep, cattle manures, sewage sludge and town waste composts, at the rate of 10, 20 or 30 tons/fed. for each. Also the inorganic fertilizer was applied at the rate of 400, 300 and 150 kg/fed. as amonium sulphate (20.5% N), calcium superphosphate (15.5% P 2 O 5 ) and potassium sulphate (48 % K 2 O), respectively (the recommended rates). The pervious treatmemts were compared with control (without fertilization). The organic fertilizers significantly increased vegetative growth characters, bulbs yield and quality. Vegetative growth characters were determined at 4 months after transplanting. Applying 30 tons/fed. of poultry manure, 20 tons/fed. of poultry manure or in organic fertilizers caused the heighest plants (without significant differences among them), in the first season. In the second season the heighest plants were obtained by adding 30 tons/fed. of poultry manure, 30 tons/fed. of sheep manure or 20 tons of poultry manure in descending order. The highest values of number of leaves and fresh weight of leaves / plant were obtained with supplying 30 tons/fed. of poultry manure or 30 tons/fed. of sheep manure, in the two seasons. Dry matter percentage of leaves and bulb fresh weight were the highest by application of 30 tons/fed. of poultry manure or 30 tons/fed. of sheep manure in the two seasons. The lowest values of bulbing ratio were obtained by addition of 30
Financial Exclusion and Poverty Reduction in Benin

By analyzing some factors related to the various constraints faced by unbanked individuals, this study explores the determinants associated with individuals without access to common financial services in Benin. It also examines the impact of the lack of access to financial services on poverty using the World Bank’s Global Findex database for 2011, 2014, and 2017. Using a probit model, we found a positive and significant relationship between financial exclusion and lack of documentation, expensive financial services, distance from financial institutions, and lack of trust in financial institutions. Moreover, individual characteristics, such as age, education level, religion, gender, and employment status are significantly associated with financial exclusion. Using a Heckman sample selection model, we show that financial exclusion in Benin has a positive and significant effect on poverty. These results are vindicated using propensity score matching (PSM) for robustness checks.
Strategic Management and Educational Dynamics of Islamic Boarding Schools in Banten

This study aims to understand the application of strategic management and dynamics in three Islamic boarding schools in Banten. This research method is qualitative research with a case study approach. Data was collected through observation, interviews, documentation, triangulation, field notes, and member verification. Data analysis was carried out using descriptive qualitative methods with deductive and inductive analysis techniques. The results showed that the strategic management carried out by these three Islamic boarding schools were as follows; prepare a system that can provide an exemplary role for all levels within the Islamic boarding school and all stakeholders in the Islamic boarding school; provide equal roles and responsibilities to human resources in Islamic boarding schools; organize student activities optimally; prepare a system that can provide an example for all levels within the Islamic boarding school environment and all stakeholders within the Islamic boarding school environment; provide equal roles and responsibilities to human resources in the cottage.
Genetic algorithm for the design of a multiband microstrip antenna with self‐avoiding geometry obtained by backtracking

The growth of small communication devices has pushed designers to design compact‐size antennas. These antennas must be low cost, lightweight, needed for mechanically robust construction, and ease of installation. In this paper, we use a novel genetic algorithm (GA) to produce an ensemble of compact self‐avoiding (SA) antennas such that the voltage standing wave ratio (VSWR) is less than 2 at the desired frequencies (as a measure of efficiency); an optimization criterion to get a desirable multiband antenna in the ultra high frequency (UHF) band. First, the electromagnetic properties of these antennas are simulated using the method of moments in MATLAB. SA antennas form a particular set of dipoles introduced here by applying a novel backtracking algorithm. We also use a Lindenmayer system that generates the geometries by a Turtle graphics render to reach our goal. Next, we simulate the VSWR for 150,000 SA antennas with lengths L from 0.1 to 0.4 m; 10 different frequencies are chosen randomly within the UHF band to obtain our results. All the VSWR ≤ 2 are clustered using density‐based spatial clustering of applications with noise algorithm (DBSCAN), so our method provides the frequency ranges where this condition is fulfilled. From this, we obtain the VSWR minimums used for the antenna design. Finally, as an instance, we use our results to select the appropriate size of a multiband antenna and, through genetic algorithms, modify the geometry to satisfy the design requirements.
Can the Sick Speak? Global Health Governance and Health Subalternity

Global Health Governance (GHG) uses a set of financial, normative, and epistemic arguments to retain and amplify its influence. During the COVID-19 pandemic, the GHG regime used its own successes and failures to prescribe more of itself while demanding further resources. However, the consistent failures of this form governance and its appeasement to a dominant neoliberal ideology lead to the following question: Is the global health governance regime failing at its goal of improving health or succeeding at other political and ideological goals that necessitate such failures? Using concepts and ideas from social theory and post-colonial studies; I examine the definitions, epistemic basis, and drivers of GHG and propose certain conditions for the legitimacy of a global health governance system. Examining historical and current cases, I find that the GHG regime currently fails to fulfil such conditions of legitimacy and instead creates spaces that limit rather than help many populations it purports to serve. Those spaces of sickness confine people and reduce them into a state of health subalternity. In being health subalterns, people’s voices are neither sought nor heard in formulating the policies that determine their health. Finally, I argue that research and policymaking on global health should not be confined to the current accepted frameworks that assumes legitimacy and benevolence of GHG, and propose steps to establish an alternative, emancipatory model of understanding and governing global health.
Tree-Structured Dilated Convolutional Networks for Image Compressed Sensing

To better recover a sparse image signal carrying redundant information from many fewer measurements than the Nyquist-Shannon sampling theorem suggested, convolutional neural networks (CNNs) can be used to emulate a compressed sensing (CS) process. However, the existing CS methods based on CNNs have the problems of high computational complexity and unsatisfactory reconstruction effect. This study aims to present a faster algorithm based on CNNs to obtain reconstructed images with finer texture details from CS measurements. A tree-structured dilated conventional network (TDCN) for image CS is proposed. To extract the image multi-scale features as much as possible for better image reconstruction, the TDCN combines tree-structured residual blocks made of three dilation convolution layers with different dilation factors; the output of each dilated convolution layer is directed to fusion layer to eliminate information loss due to the multiple cascading dilated convolutions. Moreover, L1 loss is employed as an objective optimization function instead of L2 loss to improve training results of the network and achieve better convergence. Extensive CS experiments in the study demonstrate that the proposed TDCN outperforms existing state-of-the-art methods in terms of both PSNR and SSIM at different sampling rates while maintaining a fast computational speed. Our code and the trained model are available at https://github.com/UHADS/TDCN.
An Analysis of Psychomotor Assessment Levels Based on Anderson and Krathwohl's Taxonomy in Integrated Thematic Books

This study aims to analyze the psychomotor assessment levels based on Anderson and Krathwohl's taxonomy in the integrated thematic book for grade VI, theme 5, entrepreneurship. Methods: This content analysis research used a descriptive qualitative approach. The form of research data was a distribution of psychomotor assessments, categorized according to Anderson and Krathwohl’s taxonomy. The instrument validity used was the Gregory formula. Data validity employed was increased persistence and source triangulation. Sources were obtained from the teacher's book and coursebook. Data collection techniques utilized were document studies. The data analysis technique in this study applied an interactive analysis model from Miles and Huberman. Findings: The results showed that the distribution of psychomotor assessment levels at the imitation level (P1) was 23.33%, the manipulation level (P2) was 6.67%, the precision level (P3) was 36.67%, the articulation level (P4) was 30%, and the naturalization level (P5) was 3.33%. Conclusion: Therefore, it can be concluded that the precision level of psychomotor assessment is the most common because it follows the motor development of elementary school students who are expected to do things independently.
Variable Structure Control and Its Ground Experimental Test for the Space Station Robot

Building a simulated weightless test system on the ground while making comprehensive comparisons of design controllers for a large and heavy multijointed space station robot is not an easy task. To save cost and improve the efficiency of the test, this paper develops a plan in which controllers undergo preliminary testing in a 6-DOF industrial robot. The key idea is gravity compensation included within the dynamic control algorithm of the robot to replace the function of the microgravity environment. It is generally difficult to build an accurate dynamic model for a serial-joint robot in a practical manner. Therefore, to guarantee the stability of the 6-DOF industrial robot in which the dynamic model is built inaccurately, we propose one of the simplest variable structure (VS) controllers, and the stability of the system is analyzed through the Lyapunov method. Last, experiments are carried out to provide preliminary comparisons among three potential algorithms for the space robot in a low-cost and efficient approach.
In Vivo Analysis of the Regeneration Capacity and Immune Response to Xenogeneic and Synthetic Bone Substitute Materials

Although various studies have investigated differences in the tissue reaction pattern to synthetic and xenogeneic bone substitute materials (BSMs), a lack of knowledge exists regarding the classification of both materials based on the DIN ISO 10993-6 scoring system, as well as the histomorphometrical measurement of macrophage subtypes within their implantation beds. Thus, the present study was conducted to analyze in vivo responses to both xenogeneic and synthetic bone substitute granules. A standardized calvaria implantation model in Wistar rats, in combination with established scoring, histological, histopathological, and histomorphometrical methods, was conducted to analyze the influence of both biomaterials on bone regeneration and the immune response. The results showed that the application of the synthetic BSM maxresorb® induced a higher pro-inflammatory tissue response, while the xenogeneic BSM cerabone® induced a higher anti-inflammatory reaction. Additionally, comparable bone regeneration amounts were found in both study groups. Histopathological scoring revealed that the synthetic BSM exhibited non-irritant scores at all timepoints using the xenogeneic BSM as control. Overall, the results demonstrated the biocompatibility of synthetic BSM maxresorb® and support the conclusion that this material class is a suitable alternative to natural BSM, such as the analyzed xenogeneic material cerabone®, for a broad range of indications.
Comparison of machine learning algorithms used to classify the asteroids observed by all-sky surveys

Context. Multifilter photometry from large sky surveys is commonly used to assign asteroid taxonomic types and study various problems in planetary science. To maximize the science output of those surveys, it is important to use methods that best link the spectro-photometric measurements to asteroid taxonomy. Aims. We aim to determine which machine learning methods are the most suitable for the taxonomic classification for various sky surveys. Methods. We utilized five machine learning supervised classifiers: logistic regression, naive Bayes, support vector machines (SVMs), gradient boosting, and MultiLayer Perceptrons (MLPs). Those methods were found to reproduce the Bus-DeMeo taxonomy at various rates depending on the set of filters used by each survey. We report several evaluation metrics for a comprehensive comparison (prediction accuracy, balanced accuracy, F1 score, and the Matthews correlation coefficient) for 11 surveys and space missions. Results. Among the methods analyzed, multilayer perception and gradient boosting achieved the highest accuracy and naive Bayes achieved the lowest accuracy in taxonomic prediction across all surveys. We found that selecting the right machine learning algorithm can improve the success rate by a factor of >2. The best balanced accuracy ( ∼ 85% for a taxonomic type prediction) was found for the Visible and Infrared Survey telescope for Astronomy (VISTA) and the ESA Euclid mission surveys where broadband filters best map the 1 µ m and 2 µ m olivine and pyroxene absorption bands. Conclusions. To achieve the highest accuracy in the taxonomic type prediction based on multifilter photometric measurements, we recommend the use of gradient boosting and MLP optimized for each survey. This can improve the overall success rate even when compared with naive Bayes. A merger of different datasets can further boost the prediction accuracy. For the combination of the Legacy Survey of Space and Time and VISTA survey, we achieved 90% for the taxonomic type prediction.
Youth Positive Mental Health Concepts and Definitions: A Systematic Review and Qualitative Synthesis

Background: Research on youth positive mental health (PMH) lacks comprehensiveness. We reviewed literature to (i) identify and understand concepts related to youth PMH and (ii) to summarize their definitions under broad conceptual themes. Method: We conducted a systematic review using PRISMA methodology. The protocol was registered in PROSPERO database (ID:CRD42020203712). Pubmed, Embase, PsycINFO, and OpenGrey databases were searched for publications that examined, assessed, explained, or defined PMH concepts in youth populations. Methods included searching, independent screening and review using pre-determined inclusion and exclusion criteria, extraction, coding, and iterative thematic syntheses of literature. Results: Of 3427 unique records identified, 105 articles from 26 countries met review criteria. Qualitative analysis resulted in 22 broad themes of youth PMH. These included interpersonal relationships (interpersonal competence, school connectedness, etc.), positive emotions (feel and create pleasant emotions, gratitude, etc.), self-efficacy (strengths, human agency, etc.), life satisfaction (global assessment of one’s life), and personal growth (goal achievement, life aspirations, etc.). Five novel concepts related to youth PMH were identified. Conclusions: Our review summarized and operationalized multiple concepts of youth PMH for applications in research, evaluation, and public health improvement.
Interpretation of the depths of maximum of extensive air showers measured by the Pierre Auger Observatory

To interpret the mean depth of cosmic ray air shower maximum and its dispersion, we parametrize those two observables as functions of the first two moments of the ln A distribution. We examine the goodness of this simple method through simulations of test mass distributions. The application of the parameterization to Pierre Auger Observatory data allows one to study the energy dependence of the mean ln A and of its variance under the assumption of selected hadronic interaction models. We discuss possible implications of these dependences in term of interaction models and astrophysical cosmic ray sources.