Miracle-dz/UniFAR-FTUs huggingface dataset:
Comprehensive evaluation of finger flexor tendon entheseal soft tissue and bone changes by ultrasound can differentiate psoriatic arthritis and rheumatoid arthritis.

OBJECTIVES To determine whether a detailed sonographic evaluation of the hand flexor tendon compartment could help differentiate between psoriatic arthritis (PsA) and rheumatoid arthritis (RA). METHODS Thirty-seven patients with PsA, 47 with RA and 10 healthy controls (HC) had flexor tendon (FT) compartment imaging of the dominant hand 2nd to 4th tendons using grey scale (GS) and power Doppler (PD) ultrasound (US) with evaluation for tenosynovitis, peri-tendinous lesions, soft tissue oedema and bony changes at FT insertions. 24/37 PsA and 19/47 RA cases had morning stiffness and 19/37 PsA and 10/47 RA had swollen and/or tender fingers. RESULTS Tenosynovitis was more common in PsA (25/37) despite higher DAS28 scores in RA (25/37 versus 10/45; p<0.001). Peri-tendinous dermal soft tissue oedema with associated PD signal was evident in one third of PsA patients but in no RA patients (p=0.003). Flexor tendon enthesopathy including new bone formation at the insertional site was significantly more common in PsA (p=0.001). Considering a total inflammatory score per patient summing up the three modifications of the flexor tendon (tenosynovitis, peri-tendinous oedema and insertional enthesophytes) the difference between PsA and RA remained statistically significant (p<0.001). CONCLUSIONS Our study adds to the growing body of literature that high resolution US of the hand FT compartment may help differentiate between RA and PsA, which needs assessment in the diagnostic setting.
Staged Multi-armed Bandits

In conventional multi-armed bandits (MAB) and other reinforcement learning methods, the learner sequentially chooses actions and obtains a reward (which can be possibly missing, delayed or erroneous) after each taken action. This reward is then used by the learner to improve its future decisions. However, in numerous applications, ranging from personalized patient treatment to personalized web-based education, the learner does not obtain rewards after each action, but only after sequences of actions are taken, intermediate feedbacks are observed, and a final decision is made based on which a reward is obtained. In this paper, we introduce a new class of reinforcement learning methods which can operate in such settings. We refer to this class as staged multi-armed bandits (S-MAB). S-MAB proceeds in rounds, each composed of several stages; in each stage, the learner chooses an action and observes a feedback signal. Upon each action selection a feedback signal is observed, whilst the reward of the selected sequence of actions is only revealed after the learner selects a stop action that ends the current round. The reward of the round depends both on the sequence of actions and the sequence of observed feedbacks. The goal of the learner is to maximize its total expected reward over all rounds by learning to choose the best sequence of actions based on the feedback it gets about these actions. First, we define an oracle benchmark, which sequentially selects the actions that maximize the expected immediate reward. This benchmark is known to be approximately optimal when the reward sequence associated with the selected actions is adaptive submodular. Then, we propose our online learning algorithm, for which we prove that the regret is logarithmic in the number of rounds and linear in the number of stages with respect to the oracle benchmark.
Sample Reproducibility of Genetic Association Using Different Multimarker TDTs in Genome-Wide Association Studies: Characterization and a New Approach

Multimarker Transmission/Disequilibrium Tests (TDTs) are very robust association tests to population admixture and structure which may be used to identify susceptibility loci in genome-wide association studies. Multimarker TDTs using several markers may increase power by capturing high-degree associations. However, there is also a risk of spurious associations and power reduction due to the increase in degrees of freedom. In this study we show that associations found by tests built on simple null hypotheses are highly reproducible in a second independent data set regardless the number of markers. As a test exhibiting this feature to its maximum, we introduce the multimarker -Groups TDT ( ), a test which under the hypothesis of no linkage, asymptotically follows a distribution with degree of freedom regardless the number of markers. The statistic requires the division of parental haplotypes into two groups: disease susceptibility and disease protective haplotype groups. We assessed the test behavior by performing an extensive simulation study as well as a real-data study using several data sets of two complex diseases. We show that test is highly efficient and it achieves the highest power among all the tests used, even when the null hypothesis is tested in a second independent data set. Therefore, turns out to be a very promising multimarker TDT to perform genome-wide searches for disease susceptibility loci that may be used as a preprocessing step in the construction of more accurate genetic models to predict individual susceptibility to complex diseases.
Hepatic gluconeogenic fluxes and glycogen turnover during fasting in humans. A stable isotope study.

Fluxes through intrahepatic glucose-producing metabolic pathways were measured in normal humans during overnight or prolonged (60 h) fasting. The glucuronate probe was used to measure the turnover and sources of hepatic UDP-glucose; mass isotopomer distribution analysis from [2-13C1]glycerol for gluconeogenesis and UDP-gluconeogenesis; [U-13C6]glucose for glucose production (GP) and the direct UDP-glucose pathway; and [1-2H1]galactose for UDP-glucose flux and retention in hepatic glycogen. After overnight fasting, GP (fluxes in milligram per kilogram per minute) was 2.19+/-0.09, of which 0.79 (36%) was from gluconeogenesis, 1.40 was from glycogenolysis, 0.30 was retained in glycogen via UDP-gluconeogenesis, and 0.17 entered hepatic UDP-glucose by the direct pathway. Thus, total flux through the gluconeogenic pathway (1.09) represented 54% of extrahepatic glucose disposal (2.02) and the net hepatic glycogen depletion rate was 0.93 (46%). Prolonging [2-13C1]glycerol infusion slowly increased measured fractional gluconeogenesis. In response to prolonged fasting, GP was lower (1. 43+/-0.06) and fractional and absolute gluconeogenesis were higher (78+/-2% and 1.11+/-0.07, respectively). The small but nonzero glycogen input to plasma glucose (0.32+/-0.03) was completely balanced by retained UDP-gluconeogenesis (0.31+/-0.02). Total gluconeogenic pathway flux therefore accounted for 99+/-2% of GP, but with a glycogen cycle interposed. Prolonging isotope infusion to 10 h increased measured fractional gluconeogenesis and UDP-gluconeogenesis to 84-96%, implying replacement of glycogen by gluconeogenic-labeled glucose. Moreover, after glucagon administration, GP (1.65), recovery of [1-2H1]galactose label in plasma glucose (25%) and fractional gluconeogenesis (91%) increased, such that 78% (0.45/0.59) of glycogen released was labeled (i.e., of recent gluconeogenic origin). In conclusion, hepatic gluconeogenic flux into glycogen and glycogen turnover persist during fasting in humans, reconciling inconsistencies in the literature and interposing another locus of control in the normal pathway of GP.
Exploring how innovation strategies at time of crisis influence performance: a cluster analysis perspective

ABSTRACT This paper analyzes the connection between innovation activities of companies – implemented before crisis – and their performance – measured at time of crisis. The companies listed in the STAR Market Segment of the Italian Stock Exchange are analyzed. Innovation is measured through the level of investments in total tangible and intangible fixed assets in 2006–2007, while performance is captured through growth – expressed by variations of sales, total assets and employees – profitability – through ROI or ROS – and productivity – through asset turnover or sales per employee in the period 2008–2010. The variables of interest are analyzed and compared through statistical techniques and by adopting cluster analysis. In particular, a Voronoi tessellation is also implemented in a varying centroids framework. In accord with a large part of the literature, we find that the behaviour of the performance of the companies is not univocal when they innovate.
Fire Retardant Performance of Rice Husk Ash-Based Geopolymer Coated Mild Steel - A Factorial Design and Microstructure Analysis

Higher content of silica in geopolymer coating resulted in better thermal properties. Since rice husk ash (RHA) has the highest silica content compared to other aluminosilicate sources available, it offers the best potential to be an alternative silica source in producing geopolymer coating binder. In this study, five factors including ratio of alkaline activator (AA) (A), ratio of RHA/AA (B), curing temperature (C), curing time (D) and concentration of NaOH (E) were analyzed using statistical analysis to identify the significant factors that mostly influence fire retardant performance of RHA-based geopolymer coating. The fire retardant tests were conducted and results recorded included (i) time taken to reach 300°C and (ii) temperature at equilibrium. Sample S7 (coating composition of A=5.5, B=0.3, C=50°C, D=7days, E=8M) which produced the best fire retardant performance was selected for further detailed investigation using thermogravimetry analysis (TGA) and scanning electron microscopy (SEM). It was found that the back temperature of mild steel plate of sample S7 reached 300°C after 17 minutes and achieved an equilibrium state at 398°C. SEM micrographs showed the presence of needle-like structures formed after fire test might be the reason for the best fire performance of sample S7.
Development of a systematic career coaching program for medical students

Purpose This study aimed to develop a systematic career-coaching program (SCCP) that can be used by medical teaching schools to address a growing need for career-coaching. The program objectives were to help students (1) develop a comprehensive self-understanding of their aptitudes, interests, and personality traits; (2) explore possible career choices and decide on a career path; and (3) develop the competencies needed to prepare for their future careers. Methods The SCCP was based on the ADDIE (analysis, design, development, implementation, and evaluation) model and decision-making questioning model. Medical professionals, medical education and career counseling experts, and students participated in designing the program. Results The SCCP describes coaching content, tools, operational methods, and appropriate timing, and identifies the professionals and specialists who can offer their expertise in the different coaching phases. It is designed to allow medical schools to offer the program in segments or in its entirety, depending on the curriculum and environment. Conclusion The SCCP represents a viable career-coaching program for medical students that can be applied in part or in its entirety, depending on a medical school’s curriculum and educational environment.
Numerical test of finite-size scaling predictions for the droplet condensation-evaporation transition

We numerically study the finite-size droplet condensation-evaporation transition in two dimensions. We consider and compare two orthogonal approaches, namely at fixed temperature and at fixed density, making use of parallel multicanonical simulations. The equivalence between Ising model and lattice gas allows us to compare to analytical predictions. We recover the known background density (at fixed temperature) and transition temperature (at fixed density) in the thermodynamic limit and compare our finite-size deviations to the predicted leading-order finite-size corrections.
Speed and steering angle prediction for intelligent vehicles based on deep belief network

Learning and predicting human driving behavior plays an important role in the development of advanced driving assistance systems (ADAS). Speed and steering angle which reflect the longitudinal and lateral behavior of drivers are two important parameters for behavior prediction. However, traditional behavior learning methods, especially the methods based on artificial neural networks rely on the human-selected features, and thus have poor adaptability to the highly changeable traffic environment. This paper aims to overcome this drawback by using deep learning which can learn features automatically from the driving data without human interventions. Specifically, the deep belief network (DBN) is used to build the learning model, and the training data are collected from drivers driving on the real-world road. Based on the model, the steering angle of the front wheel and the speed of vehicle are predicted. The prediction results show that, compared with the traditional learning method, DBN has a higher accuracy and can adapt to different driving scenarios with much less modifications.
Protecting web services with Service Oriented Traceback Architecture

Service oriented architecture (SOA) is a way of reorganizing software infrastructure into a set of service abstracts. In the area of applying SOA to Web service security, there have been some well defined security dimensions. However, current Web security systems, like WS-Security are not efficient enough to handle distributed denial of service (DDoS) attacks. Our new approach, service oriented traceback architecture (SOTA), provides a framework to be able to identify the source of an attack. This is accomplished by deploying our defence system at distributed routers, in order to examine the incoming SOAP messages and place our own SOAP header. By this method, we can then use the new SOAP header information, to traceback through the network the source of the attack. According to our experimental performance evaluations, we find that SOTA is quite scaleable, simple and quite effective at identifying the source.
Direct integration by synthesis and properties of single-walled carbon nanotubes

During the last decades there has been a tremendous progress in the Held of electronics and computers. The need for eheaper and faster electronic devices has been a driving force for the development of smaller functional devices. In this context, carbon nanotubes have been used as both active components (transistors, sensors) and as molccular wires in electronics. However, connecting wires to device components at the molecular scale has been one of the long-standing problems. To address this interfacing problern. it is praposed to integrate carbon nanotubes into microsystems. The approach employed here is a combination of "top-down" micromachining and "bottorn-up" direct growth of carbon nanotubes within the functional microstructure in a scalable way. As these integratcd molccules will serve as active elements in future dcviccs they must be addressable individually. The embcdded carbon nanotubes were subjected to mechanicalloads from the microsystems (or MEMS) in order to evaluatc their physical properties as nano-transducers, A process flow to integrate the nanotubes by a hybrid approach, the sclf-assembly of single-walled carbon nanotubes into surface micramachined devices, is presented. Several process integration problems were addressed, such as the unwanted selfdecomposition of the feodstock gas which resulted in an amorphous carbon overcoating. Furthermore, it was found that the micromachining of the placcholders for the nanotube self-assembly can have a strong contral over the tube Iocation, alignment and ultimatcly thcir number. In othcr words, a new method to grow individual nanotubes at defined sites in a scalablc fashion is demonstrated. In order to achicvc microelectronics-compatible nanotube integration, the process ternpcrature for the nanotube self-assembly was limited only to specific regions on the chip. In doing so, the nanotube growth was carried out globally at room temperature, while the tcmperature confinemcnt to small spots was enabled by the design of microscale hcaters. These were found to yield to important second order thermal effects. From scaling laws it was found that the Thomson effect is becoming dominant in structures featuring large thermal gradients and large current densities which increase upon downscaling. Resonant Raman scattering has been used to characterize the integratcd carbon nanotubes. The (n,m)-identification was enabled by mapping the tube-dependent scattering efficiency, i. e. the Raman intensity. In ordcr to do so, a novel statistical
Adaptive Path-loss Model-based Indoor Localization

In this paper, we present new received signal strength (RSS)-based indoor localization system. In indoor environment, it is not desirable to use a theoretical signal propagation path-loss model. The signal propagation is severally affected by surrounded object, especially metallic object. In order to cope with this problem, we introduce a new path-loss exponent estimation (PLE) node. This node generates a path-loss model appropriate for a given space. We then determine a mobile node's location based on the new path-loss model. Since PLE node operates in real time manner, it can robustly adapt the path-loss model for the circumstance. We evaluate our adaptive path-loss model-based localization system through actual experimental tests.
Robust Matrix Converter Commutation without explicit Sign Measurement

A new operation method for matrix converters is presented which eliminates the extra measuring circuits of voltage or current signs that were necessary for the commutation in the past. The paper explains the new robust method that minimises switching losses. Advantages and disadvantages of different approaches are discussed and measurements on a 5.5 kW matrix converter system are shown.
Prediction of quality using ANN based on Teaching‐Learning Optimization in component‐based software systems

The primary objective of our research work is to enhance the prediction of the quality of a component‐based software system and to develop an artificial neural network (ANN) model for the system reliability optimization problem. In this paper, we introduced the ANN‐supported Teaching‐Learning Optimization by transforming constraints to objective functions. Artificial neural network techniques are found to be powerful in the modeling software package quality metrics compared with the ancient statistical techniques. Therefore, by using the neural network, the quality characteristics of software components of the proposed work are predicted. A nonlinear differentiable transfer function of ANN used in the proposed approach is hyperbolic tangent sigmoid. A new efficient optimization methodology referred to as the Teaching‐Learning–based Optimization is proposed in this paper to optimize reliability and different cost functions. The weight values of the network are then adjusted consistent with a proposed optimization rule, therefore minimizing the network error. The proposed work is implemented in MATLAB by using the Neural Network Toolbox. The proposed work provides improved performance in terms of sensitivity, precision, specificity, negative predictive value, fall‐out or false positive rate, false discovery rate, accuracy, Matthews correlation coefficient, and rate of convergence.
Coverage and Effective Capacity in Downlink MIMO Multicell Networks With Power Control: Stochastic Geometry Modelling

In this paper, coverage probability and effective capacity in downlink multiple-antenna cellular system are considered. Two scenarios are investigated; in the first scenario, it is assumed that the system employs distance-based fractional power control with no multicell coordination. For the second scenario, we assume the system implements multicell coordinated beamforming so as to cancel inter-cell interference. For both scenarios, the BSs are assumed to randomly uniformly distributed in the area according to Poisson point process. Using tools from stochastic geometry, tractable, analytical expressions for coverage probability and effective capacity are derived for both scenarios. Numerical results reveal that for a system with stringent delay quality of service (QoS) constraints, i.e. (traffic delay is intolerable), best performance can be achieved by suitably adopting fractional power strategy when transmitting to the users, while constant power allocation performs better than all other power allocation strategies when the delay QoS constraints get loose (tolerable delay). For coverage probability, a fractional power control is better than constant power and channel inversion power strategies for low signal-to-interference plus noise ratio (SINR) thresholds, while the constant power strategy performs better than others in high SINR thresholds.
FID: Fuzzy Based Intrusion Detection for Distributed Smart Devices

Internet of Things (IoT) applications are driving the world to be smart by providing limitless services with optimized time and resources. Security and safety are paramount to ensure the reliability of IoT applications. For this purpose, Intrusion Detection Systems (IDS) must be employed in order to discover the intrusions and to contain and possibly correct their impact on the network.Reported IDS are not feasible in the context of the IoT. On the one side, rule based IDS require excessive storage cost to save and update attack signatures and they cannot detect the unknown attacks. On the other side, behavioral based IDS are more feasible in the context of IoT but they fail to detect some known attacks.In this paper, a Fuzzy based IDS is proposed where the undesired behavior is expressed using fuzzy logic. Also, after determining the fuzzy values, the decision is filtered by the Base Station. The parameters' values that influence on the proposed approach are determined following extensive simulations. Analytical study and simulation results show that the proposal outperforms existing solutions.
Phosphorus Removal by Crystallization for Scallop Shell Adsorbent

1 緒 言 ホタテ貝は,東北,北海道地域で産出され,これに伴 い年間約 21万トンのホタテ貝殻が産出され,その量は 年々増加し水産系廃棄物として問題が生じている. 青森 県においては,陸奥湾におけるホタテ貝の養殖に伴い年 間約 5万トンものホタテ貝殻が廃棄されており,ホタテ 貝殻は野積みの状態で大量に廃棄され,青森県内だけで も約 70万トン以上の量が野積みされていると推定され ている. 餌は自然界のプランクトンであるので低コスト であり,今後ホタテ貝の養殖が盛んとなりますます廃棄 量は増加すると推定される. 1) ホタテ貝殻の成分は,主に炭酸カルシウムの結晶と少 量の連続した有機質で構成されており,炭酸カルシウム の結晶は,三方晶系の方解石である. ホタテ貝殻の断面 は三層構造で構成されており,内面層は,内面に対して 垂直に数ミクロンの幅の柱状の方解石の結晶から構成さ れ,中間層は柱状の方解石の結晶束が 90°でベニヤ板の ように交差する交差版構造になっており,この層が強度 を担っている. そしてホタテ貝の内面全体は,この柱状 の結晶の先端の一部が出ており,数ミクロン程度の大き さの凹凸を形成している. 2)さらにホタテ貝殻はそのまま の状態でも,水質浄化,防虫などの効果を有するが,燃 焼させ有機物を飛ばし細かく粉砕することによって多機 能セラミック材料となることがわかっている. 3) また近年,経済発展に伴い生活排水や工業排水などが 閉鎖系水域へ大量に流れ込こみ,リン分が増加すること により引き起こされる富栄養化現象が著しく,これが微 生物や藻類の繁殖を促進し水質を低下させている. また, 排出される汚濁物質が湖沼へ流れ込むことにより汚濁が 進行し,赤潮やアオコが異常発生する. 特に,湖沼での リン塩類の増大に起因するアオコは水処理施設の運転阻 害の原因になるばかりか,水質低下や酸素欠如など水産 資源に大きな被害をもたらしている. 4) 一般的なリンの除去法として生化学的処理法や物理的 リン除法があげられる. 細菌類を用いた生物学的処理法 では,汚泥の処理や薬品コストやリン除去効率が低いと いった問題があり,課題が残されている. 5)物理学的リン 除去法には,凝集沈殿法,晶析型脱リン法などが挙げら れる. リン除去効率が高い方法は,石灰などの薬剤投下 による物理学的凝集法である. しかし,石灰使用量が多 いとヒドロキシアパタイト (HAP) の沈殿が多量に発生し リン除去後の処理が困難であるといった課題が残されて いる. 6)一方,晶析型脱リン法は過飽和を推進力とした非 平衡状態での結晶化現象を利用するリン除去法であり,7) リン除去材の表面に直接リン酸カルシウムの結晶を析出 させるため,汚泥の発生なしにリン除去が可能であり, 閉鎖系水域や水処理施設での特殊な装置なしでの利用が 可能であるといった報告がある. 以前の炭酸化したワラ ホタテ廃貝殻の有効利用による晶析型リン除去材の開発 吉 村 晃 平 塩 見 治 久 Phosphorus Removal by Crystallization for Scallop Shell Adsorbent