Miracle-dz/UniFAR-FTUs huggingface dataset:
A robust and interpretable end-to-end deep learning model for cytometry data

Significance Cytometry technologies are able to profile immune cells at single-cell resolution. They are widely used for both clinical diagnosis and biological research. We developed a deep learning model for analyzing cytometry data. We demonstrated that the deep learning model accurately diagnoses the latent cytomegalovirus (CMV) in healthy individuals. In addition, we developed a method for interpreting the deep learning model, allowing us to identify biomarkers associated with latent CMV infection. The deep learning model is widely applicable to other cytometry data related to human diseases. Cytometry technologies are essential tools for immunology research, providing high-throughput measurements of the immune cells at the single-cell level. Existing approaches in interpreting and using cytometry measurements include manual or automated gating to identify cell subsets from the cytometry data, providing highly intuitive results but may lead to significant information loss, in that additional details in measured or correlated cell signals might be missed. In this study, we propose and test a deep convolutional neural network for analyzing cytometry data in an end-to-end fashion, allowing a direct association between raw cytometry data and the clinical outcome of interest. Using nine large cytometry by time-of-flight mass spectrometry or mass cytometry (CyTOF) studies from the open-access ImmPort database, we demonstrated that the deep convolutional neural network model can accurately diagnose the latent cytomegalovirus (CMV) in healthy individuals, even when using highly heterogeneous data from different studies. In addition, we developed a permutation-based method for interpreting the deep convolutional neural network model. We were able to identify a CD27- CD94+ CD8+ T cell population significantly associated with latent CMV infection, confirming the findings in previous studies. Finally, we provide a tutorial for creating, training, and interpreting the tailored deep learning model for cytometry data using Keras and TensorFlow (https://github.com/hzc363/DeepLearningCyTOF).
The Cycle of Excellence: Using Deliberate Practice to Improve Supervision and Training

How do the good become great? Practice! From musicians and executives to physicians and drivers, aspiring professionals rely on deliberate practice to attain expertise. Recently, researchers have explored how psychotherapists can use the same processes to enhance the effectiveness of psychotherapy supervision for career-long professional development. Based on this empirical research, this edited volume brings together leading supervisors and researchers to explore a model for supervision based on behavioral rehearsal with continuous corrective feedback. Demonstrating how this model complements and enhances a traditional, theory-based approach, the authors explore practical methods that readers can use to improve the effectiveness of their own psychotherapy training and supervision. This book is the 2018 Winner of the American Psychological Association Supervision & Training Section's Outstanding Publication of the Year Award.
Total Serum Cholesterol Level in Cases of Carcinoma Breast – A Correlative Study

Aims and Objective: Correlation between serum cholesterol level and risk of breast cancer. Material and Methods: Fifty histologically diagnosed breast cancer patients were included in the study. Patients were grouped according to the size, histological type of the tumor and lymph node involvement. Patient’s total serum cholesterol levels were measured a week prior to the operation and on the 14th day postoperatively. Fifty age-matched non-cancer females were treated as a control. Observations: The pre and postoperative mean total serum cholesterol (MTSC) was found to be 272.3 ± 43.4mg/dl and 210.54 ± 31.5mg/dl respectively. An MTSC level in fifty control cases was found to be 183.42 ± 34.4mg/dl. Patients with tumor size less than 5cms showed preoperative mean serum cholesterol levels of 261.6 ± 36.5mg/dl and a postoperative value of 201.9 ± 16.9mg/dl while those with tumor size more than 10cms showed a mean serum cholesterol level of 282.36 ± 64.8mg/dl preoperatively and 211.82 ± 53.15mg/dl postoperatively. Thirty patients with scirrhous type of carcinoma had a preoperative mean serum cholesterol level as 237.36mg/dL, and twelve patients with a colloid type of carcinoma showed a preoperative level of 294.9 ± 18.4mg/dL whereas eight patients with medullary type of carcinoma showed the highest preoperative level of 324.3 ± 19.8mg/dL, whereas the corresponding postoperative values were 202.9 ± 30.0mg, 216.8 ± 27.8mg and 229.4 ± 29.8mg respectively. Conclusions: The present study helps us to conclude that dietary habits affect the association of cholesterol in breast cancer and size, histology with tumor metastasis effects such relationship.
The real effects of 'ndrangheta: firm-level evidence

We analyze the real effects of mafia infiltrations in the legal economy. We focus on the case of the 'ndrangheta, a large criminal organization originating from the South of Italy. Combining information from investigative records with panel data on firms' governance and balance sheets, we build an indicator of 'ndrangheta infiltrations in firms located in areas with no tradition of mafia settlements. We show that (i) organized crime targets firms in financial distress and privileges sectors that most rely on public sector demand or are more money laundering prone;; (ii) infiltrations generate a significant rise in the firm's revenues; (iii) the penetration of mafia produces a long-run negative effect on economic growth at the local level.
Thermal stress analysis of printed circuit heat exchanger based on thermal-structural coupling method

The supercritical carbon dioxide (S-CO2) Brayton cycle has the advantages of high efficiency, compactness and simplicity. It is expected to become the main technical route for the future advanced ship nuclear power platform. The printed circuit heat exchanger (PCHE) with ultra-high pressure, ultra-compact and ultra-high efficiency typical characteristics is the ideal configuration of the S-CO2 power generation system recuperator. The PCHE numerical analysis model is constructed and the thermal stress field of the PCHE core structure is analyzed by thermal-structural coupling method. The results show that the maximum thermal stress of the PCHE core structure is 117 MPa, which is less than the yield limit of the material and meets the requirement of strength safety. The thermal stress value of most regions in PCHE is less than 78.2MPa. Therefore, the current design scheme has a large safety margin. The PCHE compactness can be further improved by structural parameter optimization.
Inter-Regional Agricultural Virtual Water Flow in China Based on Volumetric and Impact-Oriented Multi-Regional Input-Output (MRIO) Approach

Virtual water trading is an effective strategy to alleviate water shortage. Several different methods have been developed to achieve quantitative description and evaluation of virtual water, which can be broadly divided into volumetric and impact-oriented water footprint approaches. The former focuses on the consumption of water resources, while the latter puts greater emphasis on assessing the water use impacts. Based on the volumetric and impact-oriented water footprint, this paper conducted a comprehensive study on the virtual water flow of agricultural products among regions in China. The results show that different water footprint evaluation methods have different tendencies in evaluating virtual water flow. Volumetric virtual water mainly flows from northwest and northeast China to north and east China, while impact-oriented virtual water mainly flows from northwest and central south China to east and north China. Northwest China is the largest net export region of agricultural virtual water, and it is dominated by direct water consumption. In addition, we compared the net export volume of virtual water and the water shortage situation among regions in China. North China, where the water shortage is very serious, mainly relies on external water sources, while northwest China, which also faces a water shortage problem, exports a large amount of virtual water to external sources. The findings of this study highlight the importance of taking full account of the response measures in both cases when formulating policies. In other words, the virtual water strategy should consider water quantity and water quality simultaneously.
Performance of a Hybrid Demonstration Earthquake Early Warning System in the Sichuan–Yunnan Border Region

Earthquake early warning systems (EEWSs) are considered to be one of the most effective means for seismic risk mitigation, in terms of both losses and societal resilience, by releasing an alarm immediately after an earthquake occurs and before strong ground shaking arrives the target sites to be protected. To gain experience for the National System for Fast Seismic Intensity Report and Earthquake Early Warning project, we deployed a hybrid demonstration EEWS in the Sichuan–Yunnan border region with micro-electro-mechanical system-based sensors and broadband seismographs and low-latency data transmission. In this study, we described the structure of this EEWS and analyzed its performance in the first 2 yr from January 2017 to December 2018. During this test period, the EEWS detected and processed a total of 126 ML 3.0+ earthquakes, with excellent epicentral location and magnitude estimation. The average location and magnitude estimation errors for the first alert were 4.2±7.1 km and 0.2±0.31, respectively. For the earthquakes that occurred inside and outside the hybrid network, the first alert was generated 13.4±5.1 s and 26.3±13.5 s after the origin time (OT), respectively. We analyzed the performance of the EEWS for the 31 October 2018 M 5.1 earthquake, because it was the largest event that occurred inside the hybrid network during the test period. The first alert was obtained at 7.5 s after the OT, with a magnitude error of 0.1 magnitude unit, a location error of about 1 km, and a depth error of 8 km. Finally, we discussed the main differences between the EEWS’s estimates and the catalogs obtained by the China Earthquake Network Center, and proposed improvements to reduce the reporting time. This study demonstrated that we constructed a reliable, effective hybrid EEWS for the test region, which can provide sufficient support for the design of the National EEWS project.
Paradigm Shift in Business Education: A Competence-Based Approach

The fast and unpredictable changes in the business environment lead to significant changes in the future job market. For current business students, the future will offer many new opportunities for their employment but, at the same time, it will also create many threats disguised in the disappearing jobs. Business education centered mainly on knowledge transmission is challenged to switch towards a competence-based approach which includes knowledge, skills, and attitudes. The present research focuses on the need to change the paradigm of business education by creating a new learning environment centered on business competencies, and on a new knowledge ecosystem dynamics. The approach uses both qualitative and quantitative methods. In the first phase the research is focused on a critical literature review, and extraction of ideas for the next phase based on quantitative methods. In order to evaluate the students’ perception on the need of competence-based business education, a questionnaire has been designed and applied to undergraduate and graduate students enrolled in business and management programs. Data is processed by using SPSS and deriving six logistic regressions based on the conceptual model designed similar to a hierarchy Findings coming from students show a significant awareness for the need of paradigm shift in business education, from knowledge transfer to business competence development.
Tiller dynamics in Piatã palisade grass submitted to nitrogen fertilization

The objective of this study was to determine the residual effect of nitrogen fertilization applied at the time of the waters on the demography of tillers of Urochloa brizantha cv. Piata kept under cut simulating manning continues in the dry season. The experiment was installed in the farm Capim Branco da Universidade Federal de Uberlândia (UFU), located in the city of Uberlândia, Minas Gerais. It was established the Piata grass (Urochloa brizantha cv BRS Piata) in September 2011 in an area of 9 m 2 plot -1 . The experimental design was a completely randomized block design, with four replications, with treatments distributed in a 4 x 5 factorial scheme, in which the first factor doses of urea (0, 100, 200, 400 kg ha-1 of N), demarcated in four applications always performed after the demotion of experimental units and the second factor was the time of evaluation (May, June, July, August and September). Performed the evaluations of the tillering dynamics during five months, assessing rate of appearance, mortality and survival, as well as the stability index of the population and population density, analyzing data by the method of Student-Newman-Keuls (SNK). The use of N doses did not affect the tillering of Piata grass in the dry season, due to the implementation of this have occurred with low water availability in the soil. The development of the plant is linked to the amount of water present in the soil, reducing your energy expenditure, consequently decreasing your development and production.
Efficient flexible perovskite solar cells based on a polymer additive

The rapid development of flexible perovskite solar cells (FPSCs) has attracted more and more attention. The application of FPSCs is largely in thrall to the fragility of perovskite crystals and quality of perovskite films caused by the inherent nature and uncertain grain size of perovskite. A polymer additive as an efficient strategy is utilized to restrict the fragility and improve the durability of FPSCs. In this work, we use polycaprolactone (PCL) as a polymer additive to achieve the grain boundary regulation (improving the grain size) and the desirable mechanical strength of FPSCs. A champion device based on glass/indium tin oxide (ITO) achieves high photoelectric conversion efficiency (PCE) (14.49%), which is ∼37.7% higher than that of the pristine film (10.52%). While the efficiency of FPSCs also retains 9.11%, which is 90% of the initial PCE (10.12%) after 300 bending cycles. Importantly, the PCL as a polymer additive shows great potential for future applications in wearable electronics.
Cybernetic Solutions in Analytical Management of Company’s Business Activity in Stable Growth Condi-tions

Purpose: The article is aimed at the formation of a new methodology of accounting and analytical management in business processes. The study of tasks, methods and techniques of cybernetics and refract them through the prism of algorithm of business process, gives the possibility for forecasting in stable economic growth conditions. Design/Methodology/Approach: To realize the possibilities of analyzing and forecasting resources in a business process, it is important to define the “input resources”, the infor-mation field of business processes, that is expressed in the idea of production, product characteristics data, output volume, generation of information on necessary “input re-sources" and possible“ output resources”, sales information, as well as methods of eco-nomic analysis such as marketing analysis, managerial analysis etc. and the accounts’ forecasting. Findings: To define the influence of the information field of a business process on its key indicators such as actual results, changed of human resources, acquisition, development and implementation of new technologies, there has been an accounting and analytical model developed. Its work is based on bookkeeping and economic analysis tools and a cy-bernetic feedback method. Practical Implications: The results can be implemented to forecast the outcome at each stage of business process and further on for the organization of any type of activity and any form of ownership. Originality/Value: The main contribution of this research is the generation of accounting and economic analysis tools with methods of cybernetics, which allows us to form a new scientific direction from a theoretical standpoint, and to manage business processes through the information field in practical terms.
On-Chip Optical Microresonators With High Electro-Optic Tuning Efficiency

Electro-optic tuning by using lithium niobate (LiNbO3) possesses the unique features of sub-picosecond response time, low power consumption, reduced thermal noise, and combination of nonlinear-optic applications. Here, we demonstrate a new device design and fabrication to realize on-chip electro-optically tunable LiNbO3 microresonators with high performance. This device design solves the problem of cancel-out of effective index variation induced by electro-optic effect in the microresonators made of anisotropic materials. Besides, it enables the device functions of high quality factor, polarization-selective electro-optic tuning, and large free spectral range simultaneously with few high-order modes. The microdisk structure with the air-bridge wiring produced by the standard semiconductor process facilitates the realization of integrated photonic circuits. The presented device achieves the electro-optic tuning rate up to 29.2 pm/V and the large free spectral range of 17.1 nm. The proposed device design offers highly-efficient platforms for nonlinear optics, cavity optomechanics, Kerr frequency comb generation, and cavity quantum electrodynamics.
Utilidad de la proteína C reactiva y recuento de leucocitos en sospecha de apendicitis aguda* Utility of C reactive protein and leukocyte count in suspected appendicitis

Introducción: La Apendicitis Aguda (AA) es la emergencia quirúrgica más frecuente. La proteína C reactiva (PCR) es una proteína de fase aguda que sería de utilidad en el diagnóstico de AA. El objetivo de este trabajo es determinar el rendimiento de la PCR y el recuento de leucocitos (RL) en el diagnóstico de AA. Material y Método: Estudio prospectivo entre Marzo 2002 y Julio 2003. A todo paciente ingresado con sospecha de AA se le midió PCR y RL. El diagnóstico definitivo se hizo con el estudio histopatológico. Los pacientes no operados fueron seguidos hasta un mes después del alta. Se determinó los valores promedio de cada variable y se elaboró una curva ROC para RL y PCR. Resultados: Fueron incluidos 79 pacientes (43F/36M), con un edad promedio de 29+12,5 años. El promedio de duración de los síntomas hasta el ingreso fue de 30+24 hrs. Cincuenta y dos pacientes (65%) fueron sometidos a cirugía y se confirmó AA en 46 de ellos (88%). El cálculo de curvas ROC para PCR muestra el punto de corte (mejor valor de sensibilidad y especificidad) en 2,5mg/dL, con un área bajo la curva de 0,86, mientras que el cálculo para el RL muestra un punto de corte de 12700/mm3 y un área bajo la curva de 0,73. El RL muestra mejor sensibilidad, especificidad, VPP, VPN, LR(+) y LR(–) comparado con la PCR. La combinación de PCR >2,5 mg/dL y RL >12700/mm3 mejora la especificidad, VPP y LR(+). Conclusión: El RL es más preciso que la PCR para el diagnóstico de AA.
The Effect of Image Resolution on Deep Learning in Radiography.

Purpose To examine variations of convolutional neural network (CNN) performance for multiple chest radiograph diagnoses and image resolutions. Materials and Methods This retrospective study examined CNN performance using the publicly available National Institutes of Health chest radiograph dataset comprising 112 120 chest radiographic images from 30 805 patients. The network architectures examined included ResNet34 and DenseNet121. Image resolutions ranging from 32 × 32 to 600 × 600 pixels were investigated. Network training paradigms used 80% of samples for training and 20% for validation. CNN performance was evaluated based on area under the receiver operating characteristic curve (AUC) and label accuracy. Binary output networks were trained separately for each label or diagnosis under consideration. Results Maximum AUCs were achieved at image resolutions between 256 × 256 and 448 × 448 pixels for binary decision networks targeting emphysema, cardiomegaly, hernias, edema, effusions, atelectasis, masses, and nodules. When comparing performance between networks that utilize lower resolution (64 × 64 pixels) versus higher (320 × 320 pixels) resolution inputs, emphysema, cardiomegaly, hernia, and pulmonary nodule detection had the highest fractional improvements in AUC at higher image resolutions. Specifically, pulmonary nodule detection had an AUC performance ratio of 80.7% ± 1.5 (standard deviation) (0.689 of 0.854) whereas thoracic mass detection had an AUC ratio of 86.7% ± 1.2 (0.767 of 0.886) for these image resolutions. Conclusion Increasing image resolution for CNN training often has a trade-off with the maximum possible batch size, yet optimal selection of image resolution has the potential for further increasing neural network performance for various radiology-based machine learning tasks. Furthermore, identifying diagnosis-specific tasks that require relatively higher image resolution can potentially provide insight into the relative difficulty of identifying different radiology findings. Supplemental material is available for this article. © RSNA, 2020See also the commentary by Lakhani in this issue.
Affectfullness as the basis for the (re)formulation of the teacher´s professional identity

‘Affectfullness’ is called the way of life defended by Theoretical System of Affectfullness (TSA) in which the interactions we experience in the world can become rich and meaningful. Seen in these terms, it may be understood as a method that provides parameters for analyzing our experiences and investing in our full development as human beings. As of this approach, the teaching and learning activities should also be seen from a broader perspective, since they have a relevant role in the developmental path of our species. Therefore, it is argued that in scholastic institutions, the teacher – the person in charge of ‘teaching’- needs to experience opportunities and perspectives of self-development which happens through participation in healthy interactions and appropriate conditions to carry out their work of transmitting the input of knowledge produced by humanity from generation to generation. However, unfortunately we have noticed that a large number of elementary school teachers in Brazil do not perceive themselves inserted in a context full of development possibilities, both of themselves and of their own students. Teachers experience discomfort and anxieties, which in turn result in disenchantment with their teaching activities. This paper aims to explore, based on the literature researched, some of the difficulties lived by performing teachers which were organized in seven sections that indicate how the integrity of the ‘teaching profession’ has negatively been affected. Then, it promoted a dialogue with the Theoretical System of Affectfullness (TSA) in order to elicit reflections, which contribute to the teachers arouse an “affectively expanded look” on the dimension of their daily work and their professional identity, becoming able to positively affect their work environment and help modify this reality for better.
FEASIBILITY STUDY OF ONE DISTRICT ONE FACTORY POLICY IN GHANA

Juliet Adu 1 and Emmanuel Opoku Kumi 2 . 1. School of Political Science and Public Management, University of Electronic Science and Technology of China, No.2006, Xiyuan Avenue, West Hi-Tech Zone, Chengdu, 611731, Sichuan, China. 2. Faculty of Education, University of Tasmania, Newham Campus, Launceston, Tasmania, Australia. Manuscript Info Abstract . Manuscript History Received: 12 September 2019 Final Accepted: 14 October 2019 Published: November 2019