nils-herrmann/clean_scirepeval huggingface dataset:
Physicochemical and immunochemical techniques predict the quality of diphtheria toxoid vaccines.

The most critical step in the production of diphtheria vaccines is the inactivation of the toxin by formaldehyde. Diphtheria toxoid (DTx) is produced during this inactivation process through partly unknown, chemical modifications of the toxin. Consequently, diphtheria vaccines are difficult to characterise completely and the quality of the toxoids is routinely determined with potency and safety tests. This article describes the possibility of monitoring the quality in diphtheria vaccine production with a selection of physicochemical and immunochemical tests as an alternative to established in vivo tests. To this end, diphtheria toxin was treated with increasing formaldehyde concentrations resulting in toxoid products varying in potency and residual toxicity. Differences in the quality of the experimental toxoids were also assessed with physicochemical and immunochemical techniques. The results obtained with several of these analyses, including SDS-PAGE, primary amino group determination, fluorescence spectroscopy, circular dichroism (CD) and biosensor analysis, showed a clear correlation with the potency and safety tests. A set of criteria is proposed that a diphtheria toxoid must comply with, i.e. an apparent shift of the B-fragment on SDS-PAGE, a reduction of primary amino groups in a diphtheria molecule, an increased resistance to denaturation, an increased circular dichroism signal in the near-UV region and a reduced binding to selected monoclonal antibodies. In principle, a selected set of in vitro analyses can replace the classical in vivo tests to evaluate the quality of diphtheria toxoid vaccines, provided that the validity of these tests is demonstrated in extensive validation studies and regulatory acceptance is obtained.
Planar transformer for high frequency high voltage generation applications

This paper investigates the planar transformer for high frequency high voltage (HV) generator applications. The electrical and insulation design of 2kW 400 kHz 5kV HFHV planar transformers for 2kW 35kVDC HV generator are discussed in details. A hardware prototype of 2kW 400 kHz 35kVDC HV generator with planar transformer structure is built in lab to validate the concept finally. The power density of 2kW 35kVDC HV generator with proposed high frequency HV planar transformer is higher than 2kW/L with attractive performance. The HV planar transformer is promising for high frequency HV generator applications.
Reverse club foot. Rigid and recalcitrant talipes calcaneovalgus.

We describe a congenital deformity of the foot which is characterised by calcaneus at the ankle and valgus at the subtalar joint; spontaneous improvement does not occur and serial casting results in incomplete or impermanent correction of the deformities. Experience with five feet in four children indicates that release of the ligaments and tendons anterior and lateral to the ankle and lateral to the subtalar joint is the minimum surgery necessary; subtalar arthrodesis may be required in addition. The foot deformity described may occur as an isolated condition or in association with multiple congenital anomalies. The possibility of a neurological deficit should always be excluded.
The Evolving Concept of Subjective Well-Being: The Multifaceted Nature of Happiness

1. Evolving conceptions of subjective well-being: The multifaceted nature of happiness 1.1. Concern about happiness and the good life throughout history 1.2. Chapter overview 2. Hierarchical structure: the components of SWB 2.1. Positive and negative affect 2.1.1. Frequency and intensity of positive and negative affect 2.1.2. Recommendations 2.2. Life satisfaction 2.3. Domain satisfactions 2.4. Convergent and discriminant validity of SWB components 2.5.  Temporal sequence and stages 4. Stability and consistency of SWB 5. Affect vs. cognition 6. The functioning mood system 7. Tradeoffs 8. Implications for measurement 9. Implications for research on aging 10.  the take-home message(s) and directions for future research Advances in Cell Aging and Gerontology
Algal turf scrubber (ATS) floways on the Great Wicomico River, Chesapeake Bay: productivity, algal community structure, substrate and chemistry(1).

Two Algal Turf Scrubber (ATS) units were deployed on the Great Wicomico River (GWR) for 22 months to examine the role of substrate in increasing algal productivity and nutrient removal. The yearly mean productivity of flat ATS screens was 15.4 g · m(-2)  · d(-1) . This was elevated to 39.6 g · m(-2)  · d(-1) with a three-dimensional (3-D) screen, and to 47.7 g · m(-2)  · d(-1) by avoiding high summer harvest temperatures. These methods enhanced nutrient removal (N, P) in algal biomass by 3.5 times. Eighty-six algal taxa (Ochrophyta [diatoms], Chlorophyta [green algae], and Cyan-obacteria [blue-green algae]) self-seeded from the GWR and demonstrated yearly cycling. Silica (SiO2 ) content of the algal biomass ranged from 30% to 50% of total biomass; phosphorus, nitrogen, and carbon content of the total algal biomass ranged from 0.15% to 0.21%, 2.13% to 2.89%, and 20.0% to 25.7%, respectively. Carbohydrate content (at 10%-25% of AFDM) was dominated by glucose. Lipids (fatty acid methyl ester; FAMEs) ranged widely from 0.5% to 9% AFDM, with Omega-3 fatty acids a consistent component. Mathematical modeling of algal produ-ctivity as a function of temperature, light, and substrate showed a proportionality of 4:3:3, resp-ectively. Under landscape ATS operation, substrate manipulation provides a considerable opportunity to increase ATS productivity, water quality amelioration, and biomass coproduction for fertilizers, fermentation energy, and omega-3 products. Based on the 3-D prod-uctivity and algal chemical composition demonstrated, ATS systems used for nonpoint source water treat-ment can produce ethanol (butanol) at 5.8× per unit area of corn, and biodiesel at 12.0× per unit area of soy beans (agricultural production US).
TS fuzzy controller applied to the DTC-SVM scheme for three-phase induction motor

In this paper is proposed a Takagi-Sugeno Fuzzy controller (TSF) applied to the direct torque control scheme with space vector modulation. In conventional DTC-SVM scheme, two PI controllers are used to generate the reference stator voltage vector. To improve the drawback of this conventional DTC-SVM scheme is proposed the TSF controller to substitute both PI controllers. The proposed controller calculates the reference quadrature components of the stator voltage vector. The rule base for the proposed controller is defined in function of the stator flux error and the electromagnetic torque error using trapezoidal and triangular membership functions. Constant switching frequency and low torque ripple are obtained using space vector modulation technique. Performance of the proposed DTC-SVM with TSF controller is analyzed in terms of several performance measures such as rise time, settling time and torque ripple considering different operating conditions. The simulation results shown that the proposed scheme ensure fast torque response and low torque ripple validating the proposed scheme.
Filter Bank Common Spatial Pattern (FBCSP) algorithm using online adaptive and semi-supervised learning

The Filter Bank Common Spatial Pattern (FBCSP) algorithm employs multiple spatial filters to automatically select key temporal-spatial discriminative EEG characteristics and the Naïve Bayesian Parzen Window (NBPW) classifier using offline learning in EEG-based Brain-Computer Interfaces (BCI). However, it has yet to address the non-stationarity inherent in the EEG between the initial calibration session and subsequent online sessions. This paper presents the FBCSP that employs the NBPW classifier using online adaptive learning that augments the training data with available labeled data during online sessions. However, employing semi-supervised learning that simply augments the training data with available data using predicted labels can be detrimental to the classification accuracy. Hence, this paper presents the FBCSP using online semi-supervised learning that augments the training data with available data that matches the probabilistic model captured by the NBPW classifier using predicted labels. The performances of FBCSP using online adaptive and semi-supervised learning are evaluated on the BCI Competition IV datasets IIa and IIb and compared to the FBCSP using offline learning. The results showed that the FBCSP using online semi-supervised learning yielded relatively better session-to-session classification results compared against the FBCSP using offline learning. The FBCSP using online adaptive learning on true labels yielded the best results in both datasets, but the FBCSP using online semi-supervised learning on predicted labels is more practical in BCI applications where the true labels are not available.
CHOPPER: Optimizing Data Partitioning for In-memory Data Analytics Frameworks

The performance of in-memory based data analytic frameworks such as Spark is significantly affected by how data is partitioned. This is because the partitioning effectively determines task granularity and parallelism. Moreover, different phases of a workload execution can have different optimal partitions. However, in the current implementations, the tuning knobs controlling the partitioning are either configured statically or involve a cumbersome programmatic process for affecting changes at runtime. In this paper, we propose CHOPPER, a system for automatically determining the optimal number of partitions for each phase of a workload and dynamically changing the partition scheme during workload execution. CHOPPER monitors the task execution and DAG scheduling information to determine the optimal level of parallelism. CHOPPER repartitions data as needed to ensure efficient task granularity, avoids data skew, and reduces shuffle traffic. Thus, CHOPPER allows users to write applications without having to hand-tune for optimal parallelism. Experimental results show that CHOPPER effectively improves workload performance by up to 35.2% compared to standard Spark setup.
MOVI: A Model-Free Approach to Dynamic Fleet Management

Modern vehicle fleets, e.g., for ridesharing platforms and taxi companies, can reduce passengers' waiting times by proactively dispatching vehicles to locations where pickup requests are anticipated in the future. Yet it is unclear how to best do this: optimal dispatching requires optimizing over several sources of uncertainty, including vehicles' travel times to their dispatched locations, as well as coordinating between vehicles so that they do not attempt to pick up the same passenger. While prior works have developed models for this uncertainty and used them to optimize dispatch policies, in this work we introduce a model-free approach. Specifically, we propose MOVI, a Deep Q-network (DQN)-based framework that directly learns the optimal vehicle dispatch policy. Since DQNs scale poorly with a large number of possible dispatches, we streamline our DQN training and suppose that each individual vehicle independently learns its own optimal policy, ensuring scalability at the cost of less coordination between vehicles. We then formulate a centralized receding-horizon control (RHC) policy to compare with our DQN policies. To compare these policies, we design and build MOVI as a large-scale realistic simulator based on 15 million taxi trip records that simulates policy-agnostic responses to dispatch decisions. We show that the DQN dispatch policy reduces the number of unserviced requests by 76% compared to without dispatch and 20% compared to the RHC approach, emphasizing the benefits of a model-free approach and suggesting that there is limited value to coordinating vehicle actions. This finding may help to explain the success of ridesharing platforms, for which drivers make individual decisions.
High-gain differential CMOS transimpedance amplifier with on-chip buried double junction photodiode

The transimpedance amplifier (TIA) is widely used in optical receiver circuits. The majority of CMOS TIA designs reported in the literature are intended for high speed digital signal reception. The TIA reported in this Letter is optimised for low noise analogue optical signal detection, in a situation where a weak modulated optical signal is superimposed on a large DC background. This type of signal may be encountered for example in optical coherence tomography (OCT) . Specifically, our design is optimised to detect a 100 kHz carrier frequency, 5 kHz bandwidth signal, and to reject an unwanted DC component with 50 dB attenuation compared to the signal band gain. Our TIA differs from other similar designs [2, 3] through the unique combination of an on-chip buried double junction (BDJ) photodiode, very high adjustable gain and attendant low noise.
Comorbidity of attention deficit hyperactivity disorder with conduct, depressive, anxiety, and other disorders.

Attention deficit hyperactivity disorder is a heterogeneous disorder of unknown etiology. Little is known about the comorbidity of this disorder with disorders other than conduct. Therefore, the authors made a systematic search of the psychiatric and psychological literature for empirical studies dealing with the comorbidity of attention deficit hyperactivity disorder with other disorders.



The search terms included hyperactivity, hyperkinesis, attention deficit disorder, and attention deficit hyperactivity disorder, cross-referenced with antisocial disorder (aggression, conduct disorder, antisocial disorder), depression (depression, mania, depressive disorder, bipolar), anxiety (anxiety disorder, anxiety), learning problems (learning, learning disability, academic achievement), substance abuse (alcoholism, drug abuse), mental retardation, and Tourette's disorder.



The literature supports considerable comorbidity of attention deficit hyperactivity disorder with conduct disorder, oppositional defiant disorder, mood disorders, anxiety disorders, learning disabilities, and other disorders, such as mental retardation, Tourette's syndrome, and borderline personality disorder.



Subgroups of children with attention deficit hyperactivity disorder might be delineated on the basis of the disorder's comorbidity with other disorders. These subgroups may have differing risk factors, clinical courses, and pharmacological responses. Thus, their proper identification may lead to refinements in preventive and treatment strategies. Investigation of these issues should help to clarify the etiology, course, and outcome of attention deficit hyperactivity disorder.
A framework for numeric analysis of array operations

Automatic discovery of relationships among values of array elements is a challenging problem due to the unbounded nature of arrays. We present a framework for analyzing array operations that is capable of capturing numeric properties of array elements.In particular, the analysis is able to establish that all array elements are initialized by an array-initialization loop, as well as to discover numeric constraints on the values of initialized elements.The analysis is based on the combination of canonical abstraction and summarizing numeric domains. We describe a prototype implementation of the analysis and discuss our experience with applying the prototype to several examples, including the verification of correctness of an insertion-sort procedure.
Ibuprofen plasma concentration profile in deliberate ibuprofen overdose with circulatory depression treated with therapeutic plasma exchange: a case report

Inquiries relating to ibuprofen overdose have more than tripled in the last ten years in our poison control center. Although the vast majority of cases have a benign clinical course, there are few severe or even fatal cases present with refractory circulatory failure. We describe a case of a 48 year-old male with suicidal mono-ingestion of approximately 72 g ibuprofen. Despite an initial rapid spontaneous drop in the total ibuprofen plasma concentration (IPC) from 550 to 275 mcg/mL within the first 5 h after admission, the patient developed a circulatory failure, refractory to aggressive fluid resuscitation and high doses of vasopressors. Due to ibuprofen’s favorable pharmacokinetics (>95% bound to albumin, low volume of distribution) and in the absence of specific therapeutic alternatives thereby avoiding escalating vasopressor doses, therapeutic plasma exchange (TPE) for extracorporeal elimination of ibuprofen was considered as a therapeutic rescue option. An improvement of hemodynamics with a significant reduction of vasopressors was observed with TPE-initiation. However, neither the observed IPC-profile nor a pharmacokinetic (PK) simulation provided evidence for a quantitative effective elimination of ibuprofen by TPE. Based on PK-modeling we calculated an overall ibuprofen half-life of 17.2 h for the entire observation period over 5 days. To our knowledge this is the first report of a severe ibuprofen-mono intoxication treated with TPE and providing serial IPCs over a period of five days, indicating an estimated fivefold overall-elimination half-life of 17.2 h. Despite TPE clinically improved persistent hemodynamic instability, this procedure was neither consistent with the observed IPC-profile nor correlated with a meaningful quantitative elimination of ibuprofen.
Non-orthogonal multiple access (NOMA): Concept, performance evaluation and experimental trials

Non-orthogonal multiple access (NOMA) has been attracting a lot of attention as a promising downlink multiple access scheme for LTE enhancements and 5G. This paper introduces an overview of the concept, performance evaluation gains and our experimental trials related to NOMA. The goal is to clarify the benefits of NOMA over orthogonal multiple access (OMA) such as OFDMA adopted by Long-Term Evolution (LTE), also its combination with MIMO is discussed. Using computer simulations, NOMA performance gains are assessed from both link-level and system-level perspectives. Also, our NOMA test-bed and the measurement results are explained. Our evaluation results and measurements show that NOMA provides higher gains compared to OFDMA. These gains are more than 30%.
Multithread Content Based File Chunking System in CPU-GPGPU Heterogeneous Architecture

the fast development of Graphics Processing Unit (GPU) leads to the popularity of General-purpose usage of GPU (GPGPU). So far, most modern computers are CPU-GPGPU heterogeneous architecture and CPU is used as host processor. In this work, we promote a multithread file chunking prototype system, which is able to exploit the hardware organization of the CPU-GPGPU heterogeneous computer and determine which device should be used to chunk the file to accelerate the content based file chunking operation of deduplication. We built rules for the system to choose which device should be used to chunk file and also found the optimal choice of other related parameters of both CPU and GPGPU subsystem like segment size and block dimension. This prototype was implemented and tested. The result of using GTX460(336 cores) and Intel i5 (four cores) shows that this system can increase the chunking speed 63% compared to using GPGPU alone and 80% compared to using CPU alone.
Testing for baseline differences in randomized controlled trials: an unhealthy research behavior that is hard to eradicate

According to the CONSORT statement, significance testing of baseline differences in randomized controlled trials should not be performed. In fact, this practice has been discouraged by numerous authors throughout the last forty years. During that time span, reporting of baseline differences has substantially decreased in the leading general medical journals. Our own experience in the field of nutrition behavior research however, is that co-authors, reviewers and even editors are still very persistent in their demand for these tests. The aim of this paper is therefore to negate this demand by providing clear evidence as to why testing for baseline differences between intervention groups statistically is superfluous and why such results should not be published.



Testing for baseline differences is often propagated because of the belief that it shows whether randomization was successful and it identifies real or important differences between treatment arms that should be accounted for in the statistical analyses. Especially the latter argument is flawed, because it ignores the fact that the prognostic strength of a variable is also important when the interest is in adjustment for confounding. In addition, including prognostic variables as covariates can increase the precision of the effect estimate. This means that choosing covariates based on significance tests for baseline differences might lead to omissions of important covariates and, less importantly, to inclusion of irrelevant covariates in the analysis. We used data from four supermarket trials on the effects of pricing strategies on fruit and vegetables purchases, to show that results from fully adjusted analyses sometimes do appreciably differ from results from analyses adjusted for significant baseline differences only. We propose to adjust for known or anticipated important prognostic variables. These could or should be pre-specified in trial protocols. Subsequently, authors should report results from the fully adjusted as well as crude analyses, especially for dichotomous and time to event data. Based on our arguments, which were illustrated by our findings, we propose that journals in and outside the field of nutrition behavior actively adopt the CONSORT 2010 statement on this topic by not publishing significance tests for baseline differences anymore.
Adaptive Information Dissemination in the Bitcoin Network

Distributed ledgers have received significant attention as a building block for cryptocurrencies and have proven to be also relevant in several other fields. In cryptocurrencies, this abstraction is usually implemented by grouping transactions in blocks that are then linked together to form a blockchain. Nodes need to exchange information to maintain the status of the chain which consumes significant network resources. Unfortunately, naively reducing the number of messages exchanged can have a negative impact in performance and correctness, as some transactions might not be included in the chain. In this dissertation, we study the mechanisms of information dissemination used in Bitcoin and propose a set of adaptive mechanisms that not only lowers network resource usage but can also adapt to changes in the network. Our experimental evaluation shows that is possible to lower the bandwidth consumed by 10.2% and the number of exchanged messages in 41.5%, without any negative impact in the number of transactions committed.