Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of Prediction Method for Sound Conduction Efficiency of Human Middle Ear-Application to Type IV Operation-T. Higashimachi, Y. L u and R. Toriya

When the human middle ear is damaged by various ear diseases, the linkage of the auditory ossicles may be reconstructed using the column article called the columella. In a tympanoplasty operation, the sound conduction efficiency changes according to differences in shape, material and the mounting position of the columella. We have proposed a new method for estimating the hearing restoration effect prior to the operation. In this method, a geometric model of the middle ear is constructed using SolidWorks based on CT scanning data. Frequency response characteristics of the stapes displacement in sound conduction are calculated using harmonic vibration analysis. The hearing restoration effect can be estimated by a comparison of differences in the stapes displacement between the reconstruction model and a healthy subject. In the case in which the stapes remains in a normal shape, including the horseshoe portion, the type III operation is performed. In the case in which only the basal plane of the stapes is left, the type IV operation is performed. With the type IV operation, it is more difficult to improve hearing ability than with the type III operation. In the type III model, various verifications have been carried out on the validity of our prediction method. In this study, the validity of our method is verified for the type IV model. On the other hand, the audiogram is made by precise audiometry in the medical field. The audiogram is the record of the value of hearing level at every frequency in the hearing test. Using our proposed calculation formula, the audiogram of the type IV operation model was made. The degree of hearing amelioration can also be evaluated quantitatively in the type IV model prior to an operation. Through this study, the optimization of reconstruction of the middle ear using the columella becomes possible.
EvoFlows: an Interactive Approach for Visualizing Spatial and Temporal Trends in Origin-Destination Data

A BSTRACT Origin-Destination (OD) datasets describe the movement of entities between different geographic locations over time, such as human migration, movement of animals or diseases, trafﬁc movement, etc. Visualizing the spatio-temporal patterns underlying OD databases is a challenging task since it involves the study of ﬂows between spatial locations (origins and destinations) in a temporal context. Resulting from a collaborative effort of computer scientists and social scientists, our new visualization tool, EvoFlows, combines and synchronizes two complementary views. The ﬁrst one relies on a system for visualizing time series data, MultiStream, and highlights the temporal dimension of OD data. It depicts inﬂows and outﬂows as aggregated stacked time series. Relying on ﬂow maps, the second one highlights the geographic dimension and magnitude of ﬂows at a given time-stamp. Our approach allows the temporal and spatial exploration of the ﬂows at different levels of detail through multiple interaction techniques, visual components, and synchronized animations. The practical usability is illustrated by analyzing data on refugee migration over a period of 59 years.
Effects of anxiety sensitivity on nicotine dependence and smoking cessation success

Amaç: Bu çalışmada, Sigara Bırakma Polikliniğine başvuran hastalarda anksiyete duyarlılık düzeyleri ile nikotin bağımlılığı ile sigara bırakma sonuçları arasındaki ilişkiyi araştırmayı amaçladık. Yöntem: Bu retrospektif çalışma Ocak 2017-Temmuz 2017 tarihleri arasında sigara bırakma polikliniğine başvuran 286 hastayı içermektedir. Sosyo-demografik özellikler, sigara içme durumu, Nikotin Bağımlılığı için Fagerström Testi (FTDN) skorları, Beck Depresyon Envanteri (BDI) ile ölçülen depresyon skorları ve Beck Anksiyete Envanteri (BAI) ve Anksiyete Duyarlılığı İndeksi-3 (ASI) ölçeklerinin skorları hasta tıbbi dosyalarından geriye dönük olarak alındı. Tüm hastalar ile irtibata geçildi ve hastaların anlık sigara içme durumu kaydedildi. Bulgular: Katılımcıların % 19,5'i (n = 56) (izlemeye gelmeyenler dahil) sigarayı bırakmış ve sigarayı bırakma tarihinden en az altı ay sonra hala içmemektedirler. Ortalama anksiyete duyarlılığı skorları orta / yüksek nikotin bağımlı hastalarda hafif nikotin bağımlı hastalardan anlamlı derecede yüksekti (sırasıyla p = 0.001 ve p <0.001). Anksiyete duyarlılığı ve tüm alt ölçeklerinin ortalama puanları, mevcut sigara içicilerin sigara içenlere göre anlamlı derecede yüksekti (her biri için p <0.001). Sonuç: Anksiyete duyarlılığının sigara bırakma başarısında ciddi bir engel olabileceği belirlenmiştir. Bununla birlikte, kaygı duyarlılığı, yüksek nikotin bağımlılığı ile anlamlı şekilde ilişkilidir. Sigarayı bırakmayı planlayan hastaların ilk günlerinden kaygı duyarlılığı, kaygı ve depresyon düzeylerini değerlendirmek önemlidir. Yüksek kaygı duyarlılığına sahip sigara içicileri dikkatle izlenmeli ve bırakma oranlarını artırmak için kaygı hassasiyetlerini azaltmak için tedaviler uygulanmalıdır.
Study on the Intelligent Selection Model of Fuzzy Semantic Optimal Solution in the Process of Translation Using English Corpus

In order to improve the accuracy and reasonableness of using English corpus for translation, a method of using English corpus to perform translation tasks based on fuzzy semantic optimal solution intelligent selection and inspired computing for wireless networks is proposed. The information extraction model using English corpus for translation is constructed, and the fuzzy semantic keyword feature directivity model of English corpus translation is established. Fuzzy semantic ontology feature registration method is used to calculate the fuzzy semantic intelligence optimal solution vector in English translation. The semantic fuzzy feature matching and adaptive subject word registration are realized in English translation. The fuzzy link relation of semantic ontology is established, and the fuzzy semantic optimal solution is obtained. The accuracy of machine translation in English corpus is improved. The experimental results show that the fuzzy semantic optimal solution has better registration performance and the feature matching degree of the subject words is higher, which improves the reasonableness and accuracy of translation in English corpus. At the same time, it provides a new idea for intelligent computation and recognition of wireless network.
New Rhinocerotidae from the Kisingiri Localities (Lower Miocene of Western Kenya)

ABSTRACT We describe new material of Rhinocerotidae recently collected in western Kenya. A skull from Karungu is one of the best-preserved Miocene skulls in Africa. It differs substantially from that of Rusingaceros leakeyi, the only other relatively well-known rhino from this region and age, in its degree of brachycephaly, possession of a deep nasal notch, and long nasal bones that probably carried a horn of moderate size. Miocene African rhinos are still too poorly known to resolve their phylogenetic relationships, but we tentatively assign this skull to a new species of Victoriaceros, a genus whose type species comes from the younger site of Maboko, although the Karungu skull has a much smaller nasal horn. A parsimony analysis resolves them as sister species within the Elasmotheriini, close to the other African genera Turkanatherium and Chilotheridium, but we consider this result debatable, as Victoriaceros differs considerably from them. Still, they might all be descended from European forms. A partial skull from Gumba is assigned to the Aceratheriini, making it one of the earliest representatives of this group and suggesting that the origin of this tribe could be African.
Control System for a Tracked Mobile Robot- Acronym

This thesis deals with development of a control system for a tracked mobile robot. Firstly, the task of Simultaneous Localization And Mapping (SLAM) is briefly introduced and main SLAM approaches are described. As the main part of the thesis, the control system is designed and implemented in Robot Operating System (ROS). It consists of path planning, motion control and exploration. As a result, the developed robotic system is able to semi-autonomously explore and map the unknown environment. Finally, the presented solution was tested in real world experiments.
Determinants of Job Satisfaction on Firefighters after 2017 Pohang Earthquake

In order to understand the determinants of job satisfaction of firefighters in Pohang, Korea, this study considered prior studies, designed a research model, and demonstrated the hypothesis. The results of the study are summarized as follows. First, most of the firefighters put into 2017 Pohang earthquake have a working experience less than 10 years, the ages were in their 30s and 40s. Moreover, the subjects’ education levels were higher than higher education. Second, what influenced job satisfaction was in order of compensation, conflict within an organization and workload. The results showed that high level of stress and exposure from the post-traumatic stress disorder were the influential factors of compensation. Conflicts within organization has been caused by differences in thought and behavior among the members, limited resources and polices. It is observable that following the law or the procedures even in an emergency, in addition to provide protection and prevention services affected workload. Third, job characteristics did not have significant impact on job satisfaction. Difficulties from emergency dispatch, irregular life pattern and etc. affected more negatively than having self-esteem from being a firefighter. -------------------------------------------------------------------------------------------------------------------------------------Date of Submission: 08-07-2020 Date of Acceptance: 23-07-2020 -------------------------------------------------------------------------------------------------------------------------------------
IMPROvING AN ICu DAILy GOALS ChECKLIST: INTEGRATED AND END-Of-GRANT KNOWLEDGE TRANSLATION

Can Respir J Vol 22 No 2 Mar/Apr 2015 81 CONCLUSION: The WAVE Score demonstrates improved performance, including sensitivity (ability to correctly detect extubation failure), in patients whom were less sedated (RASS ≥ −1). While sedation is known to reduce RRV in general, these findings suggest sedation may also blunt the capacity of the WAVE score (due to reduced RRV) to detect inability to tolerate an increased workload of breathing during an SBT. The WAVE score performance appears to perform superiorly in patients with a high risk of failure based on elevated RSBI or RR. The WAVE Score demonstrated stable performance when changing the definition of time (12-72 hrs) before reintubation. The clinical impact of providing the WAVE score to clinicians sequentially up to the time of extubation remains to be determined. REFERENCES 1. Evidence-based guidelines for weaning and discontinuing ventilatory support: A collective task force facilitated by the American College of Chest Physicians; the American Association for Respiratory Care; and the American College of Critical Care Medicine. Chest 2001;120(6 Suppl):375S. 2. Miu T, Joffe AM, Yanez ND, et al. Predictors of reintubation in critically ill patients. Respir Care 2014;59:2. 3. Ely EW, Baker AM, Evans GW, Haponik EF. The prognostic significance of passing a daily screen of weaning parameters. Intens Care Med 1999;25:581. 4. Esteban A, Frutos F, Tobin MJ, et al. A comparison of four methods of weaning patients from mechanical ventilation. Spanish Lung Failure Collaborative Group. N Engl J Med 1995;332:345. 5. Brochard L, Rauss A, Benito S, Conti G, Mancebo J, Rekik N, Gasparetto A, Lemaire F. Comparison of three methods of gradual withdrawal from ventilatory support during weaning from mechanical ventilation. Am J Respir Crit Care Med 1994;150:896. TAble 1 Wave score subgroup analysis Subgroups SeN SPe PPV NPV AUC P-value (AUC) # Failed extubation # Passed extubation Total RSBI ≥110 1.00 0.50 0.36 1.00 0.93 0.01 5 18 23 RSBI <110 0.71 0.59 0.18 0.94 0.70 45 346 391 Age ≥60 0.83 0.54 0.19 0.96 0.77 0.30 30 234 264 Age <60 0.62 0.63 0.19 0.92 0.68 21 150 171 RASS ≥−1 0.78 0.58 0.20 0.95 0.75 0.15 41 305 346 RASS <−1 0.56 0.54 0.13 0.91 0.58 9 76 85 RR ≥30 1.00 0.52 0.48 1.00 0.85 0.02 14 31 45 RR <30 0.65 0.58 0.14 0.94 0.65 37 346 383 TAble 2 Test characteristics of wave score RSbI, RR All patients SeN SPe PPV NPV AUC/ bACC* #Failed extubation # Passed extubation Total
Four-Dof PKM with Articulated Travelling-Plate

This paper discusses some ways to achieve large tilting motions with PKM by resorting to articulated travelling plate. Different known options are firstly presented: remote actuation, hybrid architectures, redundancy, rotation amplification, and translation-to-rotation transformation. Starting from two of those features, the aim of this paper is to go one step further and to analyse various ways to obtain 4-dof robots which compare directly with commercially available Delta-like robots in terms of technology, workspace, and performance while avoiding the central, telescopic, RUPUR kinematic chain.
Nonlinear Adaptive Control of a pH Process

In this paper a nonlinear adaptive control method is presented for a pH process, which is difficult to control due to the nonlinear and uncertainties. A theoretical and experimental investigation was conducted of the dynamic behavior of neutralization process in a continuous stirred tank reactor (CSTR). The process control was implemented using different control strategies, velocity form of PI control and nonlinear adaptive control. Through simulation studies it has been shown that the estimated parameters are in good agreement with the actual values and that the proposed adaptive controller has excellent tracking and regulation performance.
Visual Landmark Recognition with Deep Learning

In this work we deal with instance recognition using deep learning. For extracting global descriptors we use neural network model trained with metric learning approach. Various modifications to k-NN classifiers to improve recognition quality were created. We also experiment with using multiple descriptors extracted from rescaled images. To simulate real world application we evaluate the model on created dataset referred to as Tini GLD. We achieved 0.84 Micro Average precision when using multiple descriptors.
Regional linkages between raised bogs and the climate, groundwater, and landscape of north-western Minnesota

1 Landsat imagery was used to map the distribution of 127 raised bogs in northwestern Minnesota. Bogs collectively cover 1236 km2 (16% of the study area) despite the relatively dry regional climate and periodic droughts. 2 The physical, chemical, and biotic properties of these bogs have no apparent relationship to the westward climatic gradient indicating a high degree of buffering from changes in moisture stress. 3 Most bogs are located where groundwater discharge moderates moisture losses to the atmosphere and may decouple bogs from a direct climatic control. Bogs are also consistently related to physiographic features, such as drainage divides, interfluves of tributary streams, and beach ridges that constrain the surface and groundwater hydrology. 4 During droughts groundwater moves upward through the peat column toward the depressed water table, which is located 1-2 m below the peat surface. During moist periods, however, water-table mounds within these bogs drive surface water downward deflecting the deeper upwardly moving groundwater laterally to the bog margins. 5 Such short-term reversals in flow have little effect on the pore-water chemistry of major cations, which reflect the predominant downward flow over the past decade. Several chemical species, however, behave nonconservatively and respond more directly to climatic change. 6 Discharge zones for groundwater seem to be an essential prerequisite for bog formation in arid regions. Peat accumulation should be most rapid over discharge zones, which can maintain water table mounds, even during droughts Once a peat mound has formed, its higher water table will drive local recharge cells, which isolate the vegetation from groundwater and facilitate the development of a raised bog.
Seismic Performance Assessment of Reinforced Concrete Frame-Shear Wall Structures in Hydropower Plants Based on Material Damage

For the reinforced concrete frame-shear wall (RCF-SW) structures in hydropower plants (HPs), the tensile cracking and compressive crushing of the reinforced concrete (RC) members are considered as the main potential damage. This paper presents a methodology to assess the seismic performance of RCF-SW structures. In this methodology, a concrete damage plasticity model is employed to simulate the reinforced concrete, and the structural seismic responses are investigated through nonlinear incremental dynamic analysis (IDA). Several engineering demand parameters (EDPs) based on the material damage are proposed to identify the structural engineering limit states and damage states at the member level. The case of x HP is provided as an example to illustrate the methodology and discuss the probable nonlinear response and structural damage state. The concrete damage evolution, reinforcement stresses, and drift ratios of the RCF-SW structure are presented, and the engineering limit states and structural damage states are identified. In comparison with the drift ratio index, the EDPs based on material damage are more suitable for identifying the damage state of the RCF-SW structure, whose damage is controlled by the damage of the RC members.
Batch mode active learning for mitotic phenotypes using conformal prediction

Machine learning models are now ubiquitous in all areas of data analysis. As the amount of data generated continues to increase exponentially, the task of annotating suﬃcient objects with known labels by an expert remains expensive. To mitigate this, active learning approaches attempt to identify those objects whose labels will be most informative. Here, we introduce a batch-based active learning framework in a pooled setting based around conformal predictors. We select objects to add to the labelled observations based on perceived novelty, while mitigating the risks of selecting highly correlated or outlying observations. We compare our approach to classical methods using an example UCI dataset, and demonstrate its application to a pharmaceutically relevant cellular imaging problem for classifying mitotic phenotypes. Our approach facilitates eﬃcient discovery of rare and novel classes within large screening datasets.
Heavy-tailed longitudinal regression models for censored data: A likelihood based perspective

HIV RNA viral load measures are often subjected to some upper and lower detection limits depending on the quantification assays. Hence, the responses are either left or right censored. Moreover, it is quite common to observe viral load measurements collected irregularly over time. A complication arises when these continuous repeated measures have a heavy-tailed behaviour. For such data structures, we propose a robust censored linear model based on the scale mixtures of normal distributions (SMN family). To take into account the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is considered. A stochastic approximation of the EM algorithm (SAEM algorithm) is developed to obtain the maximum likelihood estimates of the model parameters. The main advantage of this new procedure allows us to estimate the parameters of interest and evaluate the log-likelihood function in an easy and fast way. Furthermore, the standard errors of the fixed effects and predictions of unobservable values of the response can be obtained as a by-product. The practical utility of the proposed methodology is exemplified using both simulated and real data.
Ozone affected by a succession of four landfall typhoons in the Yangtze River Delta, China: major processes and health impacts

Abstract. Landfall typhoons can significantly affect O3 in the Yangtze River Delta (YRD) region. In this study, we investigate a unique case characterized by two multiday regional O3 pollution episodes related to four successive landfall typhoons in the summer of 2018 in the YRD. The results show that O3 pollution episodes mainly occurred during the period from the end of a typhoon to the arrival of the next typhoon. The time when a typhoon reached the 24 h warning line and the time when the typhoon dies away in mainland China can be roughly regarded as time nodes. Meanwhile, the variations of O3 were related to the track, duration and landing intensity of the typhoons. The impact of typhoons on O3 was like a wave superimposed on the background of high O3 concentration in the YRD in summer. When a typhoon was near the 24 h warning line before it landed on the coastline of the YRD, the prevailing wind originally from the ocean changed to be from inland, and it transported lots of precursors from the polluted areas to the YRD. Under influences of the typhoon, the low temperature, strong upward airflows, more precipitation and wild wind hindered occurrences of high O3 episodes. After the passing of the typhoon, the air below the 700 hPa atmospheric layer was warm and dry, and the downward airflows resumed. The low troposphere was filed with high concentration of O3 due to O3-rich air transported from the low stratosphere and strong photochemical reactions. It is noteworthy that O3 was mainly generated in the middle of the boundary layer (∼ 1000 m) instead of at the surface. High O3 levels remained in the residual layer at night, and would be transported to the surface by downward airflows or turbulence by the second day. Moreover, O3 can be accumulated and trapped on the ground due to the poor diffusion conditions because the vertical diffusion and horizontal diffusion were suppressed by downward airflows and light wind, respectively. The premature deaths attributed to O3 exposure in the YRD during the study period were 194.0, more than the casualties caused directly by the typhoons. This work has enhanced our understanding of how landfall typhoons affect O3 in the YRD and thus can be useful in forecasting O3 pollution in regions strongly influenced by typhoon activities.
UTILITY MAXIMIZATION WITH INFINITELY MANY ASSETS

We study the problem of utility maximization from terminal wealth in a semimartingale model with countably many assets. After discussing in this context the appropriate notion of admissible strategy, we give a characterization result for the superreplication price of a contingent claim. Utility maximization problems are then studied with the convex duality method, and we extend finite-dimensional results to this setting. The existence of an optimizer is proved in a suitable class of generalized strategies: this class has also the property that maximal utility is the limit of maximal utilities in finite-dimensional submarkets. Counterexamples are then given, which illustrate several phenomena which arise in presence of infinitely many assets. MSC: Primary: 60H30, 91B28; Secondary 60H05, 60G48