nils-herrmann/clean_scirepeval huggingface dataset:
Buying and selling human eggs: infertility providers' ethical and other concerns regarding egg donor agencies
Venue: BMC medical ethics

BackgroundEgg donor agencies are increasingly being used as part of IVF in the US, but are essentially unregulated, posing critical ethical and policy questions concerning how providers view and use them, and what the implications might be.MethodsThirty seven in depth interviews of approximately 1 h were conducted with 27 IVF providers and 10 patients.ResultsClinicians vary in their views and interactions concerning egg donor agencies, ranging widely in whether and how often they use agencies. Agencies may offer egg recipients increased choices, but raise ethical and other concerns regarding respect for donors as individuals (e.g. adequacy of informed consent) potential harms, justice (e.g. concerns about possible eugenics by encouraging and facilitating selection and marketing of facts for offspring) and donors constituting a vulnerable group. The quality of agencies appears to vary considerably, from acceptable to problematic. Agencies' medical and psychological screenings of donors can range, and be minimal. Not all agencies adequately track donors' prior numbers of donations, or share the relevant records with clinics. Clinics may find that potential donors have genetic mutations and medical problems about which they were unaware. Yet agencies and clinics do not provide care for such donors, generating stress. Dissemination of donors' personal data can potentially threaten confidentiality. Questions emerge of whether increased monitoring/oversight of agencies may be beneficial.ConclusionsThese data, the first to examine providers' views and interactions regarding egg donor agencies, suggest wide variations in quality and use of agencies, and have critical implications for practice, policy, education and research. Given the potential limitations of the current model of self regulation of agencies, the present data suggest needs to consider stronger professional guidelines or possible governmental regulations to establish, require and enforce higher standards for agencies to follow, regarding advertising to potential donors and recipients, arranging for appropriate informed consent concerning risks and benefits involved, and for quality control. Appropriate informed consent should be obtained from potential egg donors, including the fact that they may learn about mutations or medical problems about which they were unaware, but for which they will not receive treatment as part of this process. Enhancing understanding among the public at large about what egg donation entails may also be helpful.
[Risk of perinatal complication and egg donation: Role of resorting to cross border care?
Venue: Journal de gynecologie, obstetrique et biologie de la reproduction

In France, egg donation is covered by Social insurance among women<43 years old. Because of shortage of egg donor, women aged 43 years or more cannot resort to egg donation in French infertility centers, leading them to turn to the foreign centers having practices different and less regulated than in France. We are thus brought to take care of the pregnancy and of the delivery of these women. Our objective was to estimate if the perinatal risks are more important after egg donation abroad than in case of egg donation in a French center.  Retrospective study between January, 2010 and April, 2013, comparing women having had an egg donation to Cochin then having delivered in the maternity hospital of their choice (n=88) and the women having had an egg donation abroad then having delivered in the Port Royal maternity (n=121) First, the modalities of egg donation were compared between the Cochin hospital and the foreign centers. Second, the obstetric and perinatal outcomes were compared between both groups, then by stratifying according to the type of pregnancy (singleton or multiple) RESULTS Among women having had an egg donation abroad, the age of the donor was lower (25.7 vs. 31.7, P=0.001) the average number of embryos transferred higher (2.1+ 0.6 vs. 1.7+ 0.5, P=0.001) and the rate of multiple pregnancies higher (47.9% vs. 9.1% P=0.001) than among women having had an egg donation at Cochin. We observed after egg donation abroad compared to egg donation at Cochin, a birth weight significantly lower (2678+ 745g vs. 3045+ 682g, P=0.001) and a prevalence of intrauterine growth retardation higher (11.1% vs. 4.2% P=0.04) Among singletons, abnormal placentation was more frequent in case of egg donation abroad (17.5% vs. 5.1% P=0.02) In case of twin pregnancy, we highlighted very high rates of complications, without significant difference according to the place where egg donation was practiced.  We observed an increased risk of intrauterine growth retardation after egg donation abroad, which could essentially be explained by the association between advanced maternal age and multiple gestation. For other obstetric and perinatal complications, the differences between both groups were less important than expected, but very high in both groups, whether the egg donation was realized in France or abroad. The complications seem mainly due to the multiple gestations, justifying the transfer of a single embryo whenever possible.
Successful pregnancy with donor eggs in vitro fertilization after premature ovarian insufficiency in a tertiary hospital in a low income setting: a case report
Venue: Fertility Research and Practice

BackgroundPremature Ovarian Insufficiency (POI) is classically defined as 4 6 months of cessation of menses (amenorrhea) in women under 40, associated with menopausal level of serum gonadotropins FSH 40 IU/L and hypo estrogenism and is also referred to as hypergonadotropic hypogonadism. This disorder can manifest as primary amenorrhea without the onset of menses (menarche) or as secondary amenorrhea after menarche and pubertal development. The diagnosis of this condition in Cameroon is sometimes difficult because of the high cost of hormonal assays and the few laboratories offering these services.Case presentationThe patient was a 38 year old G2P0020, blood group O Rh positive, genotype AA and BMI 19 kg/m2 who came to our service because of secondary amenorrhea and infertility of 2 years' duration. She has a history of pulmonary tuberculosis that was treated in Cameroon. After laparoscopy and hormonal profile, the diagnosis of premature ovarian insufficiency was reached. The woman underwent a successful donor egg in vitro fertilization cycle and delivered a female fetus. Two years later YE requested IVF with autologous eggs, which was not possible, and since then she has remained with one child.ConclusionThe diagnosis of premature ovarian insufficiency is difficult in Cameroon because of the high cost of laboratory investigations and difficult access to the tests. In vitro fertilization with donor egg is a better treatment option. Unfortunately, it is not accessible to most Cameroonians because of lack of technical ability and the existence of cultural and financial barriers.
Profiles In Caregiving The Unexpected Career

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Deep Structured Energy Based Models for Anomaly Detection
Venue: ICML

In this paper, we attack the anomaly detection problem by directly modeling the data distribution with deep architectures. We propose deep structured energy based models (DSEBMs) where the energy function is the output of a deterministic deep neural network with structure. We develop novel model architectures to integrate EBMs with different types of data such as static data, sequential data, and spatial data, and apply appropriate model architectures to adapt to the data structure. Our training algorithm is built upon the recent development of score matching \cite{sm} which connects an EBM with a regularized autoencoder, eliminating the need for complicated sampling method. Statistically sound decision criterion can be derived for anomaly detection purpose from the perspective of the energy landscape of the data distribution. We investigate two decision criteria for performing anomaly detection: the energy score and the reconstruction error. Extensive empirical studies on benchmark tasks demonstrate that our proposed model consistently matches or outperforms all the competing methods.
A Review of 40 Years of Cognitive Architecture Research: Focus on Perception, Attention, Learning and Applications
Venue: ArXiv

In this paper we present a broad overview of the last 40 years of research on cognitive architectures. Although the number of existing architectures is nearing several hundred, most of the existing surveys do not reflect this growth and focus on a handful of well established architectures. While their contributions are undeniable, they represent only a part of the research in the field. Thus, in this survey we wanted to shift the focus towards a more inclusive and high level overview of the research in cognitive architectures. Our final set of 86 architectures includes 55 that are still actively developed, and borrow from a diverse set of disciplines, spanning areas from psychoanalysis to neuroscience. To keep the length of this paper within reasonable limits we discuss only the core cognitive abilities, such as perception, attention mechanisms, learning and memory structure. To assess the breadth of practical applications of cognitive architectures we gathered information on over 700 practical projects implemented using the cognitive architectures in our list. We use various visualization techniques to highlight overall trends in the development of the field. For instance, our data confirms that the hybrid approach to cognitive modeling already dominates the field and will likely continue to do so in the future. Our analysis of practical applications shows that most architectures are very narrowly focused on a particular application domain. Furthermore, there is an apparent gap between general research in robotics and computer vision and research in these areas within the cognitive architectures field. It is very clear that biologically inspired models do not have the same range and efficiency compared to the systems based on engineering principles and heuristics. Another observation is related to a general lack of collaboration, which is surprising to see in the inherently interdisciplinary area of cognitive architectures. Several factors hinder communication, among which are the closed nature of the individual projects (only one third of the reviewed here architectures are open source) and terminological differences.
Semantic Filtering
Venue: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)

Edge preserving image operations aim at smoothing an image without blurring the edges. Many excellent edge preserving filtering techniques have been proposed recently to reduce the computational complexity or/and separate different scale structures. They normally adopt a user selected scale measurement to control the detail/texture smoothing. However, natural photos contain objects of different sizes which cannot be described by a single scale measurement. On the other hand, edge/contour detection/ analysis is closely related to edge preserving filtering and has achieved significant progress recently. Nevertheless, most of the state of the art filtering techniques ignore the success in this area. Inspired by the fact that learning based edge detectors/classifiers significantly outperform traditional manually designed detectors, this paper proposes a learning based edge preserving filtering technique. It synergistically combines the efficiency of the recursive filter and the effectiveness of the recent edge detector for scale aware edge preserving filtering. Unlike previous filtering methods, the propose filter can efficiently extract subjectively meaningful structures from natural scenes containing multiple scale objects.
Trends in Long Term Outcomes Among Patients With Antineutrophil Cytoplasmic Antibody Associated Vasculitis With Renal Disease
Venue: Arthritis rheumatology

It is still not clear how advances in the management of antineutrophil cytoplasmic antibody (ANCA) associated vasculitis (AAV) have impacted long term outcomes. We undertook this study to examine changes over 25 years in long term clinical outcomes, including the impact of renal function at diagnosis (a potential marker of time to disease detection) and the duration of cyclophosphamide use in AAV patients with renal involvement.
A Narrative Inquiry of Protest Songs: Comparing the Anti War Music of Vietnam and Iraq

This research examines the social role of protest music in wartime eras through lyrical content analysis. By analyzing songs across the Vietnam War era and the Iraq War era, the shifting role of protest music across generations reveals not only how this music influences and encourages different social aggregates, but also how it adapts to remain relevant in a continuously modernizing American society. This research thus serves to demonstrate the impact of narratives in social movements and the sway narratives have in shaping public perspectives through their encouragement of solidarity between diverse social groups. Methodology includes narrative analysis of two representative samples of protest music pertinent to each of the two war eras, and qualitative lyrical examination of these songs in comparison and contrast both within and across each era. This method of narrative analysis utilizes the structure of formula stories as a model for determining the effect of protest music through symbolic and emotion codes present in the lyrical melodramas, and how these melodramas depict the need for protest and anti war sentiment by serving as passionate calls to action behind which audiences belonging to diverse social aggregates can rally in solidarity.
Drag reduction on laser patterned hierarchical superhydrophobic surfaces.
Venue: Soft matter

Hierarchical laser patterned surfaces were tested for their drag reduction abilities. A tertiary level of surface roughness which supports stable Cassie wetting was achieved on the patterned copper samples by laser scanning multiple times. The laser fabricated micro/nano structures sustained the shear stress in liquid flow. A rheometer setup was used to measure the drag reduction abilities in term of slip lengths on eight different samples. A considerable increase in slip length (111% on a grate sample) was observed on these surfaces compared to the slip length predictions from the theoretical and the experimental models for the non hierarchical surfaces. The increase in slip lengths was correlated to the secondary level of roughness observed on the patterned samples. The drag reduction abilities of three different arrangements of the surface features were also compared: posts in a square lattice, parallel grates, and posts in a hexagonal lattice. Although the latter facilitates a stable Cassie state, it nevertheless resulted in a lower normalized slip length compared to the other two arrangements at a similar solid fraction. Furthermore, we coated the laser patterned surfaces with a silane to test the effect of surface chemistry on drag reduction. While the contact angles were surprisingly similar for both the non silanized and the silanized samples, we observed higher slip lengths on the latter, which we were able to explain by measuring the respective penetration depths of the liquid vapour interface between surface features.
Agri IoT: A semantic framework for Internet of Things enabled smart farming applications
Venue: 2016 IEEE 3rd World Forum on Internet of Things (WF IoT)

With the recent advancement of the Internet of Things (IoT) it is now possible to process a large number of sensor data streams using different large scale IoT platforms. These IoT frameworks are used to collect, process and analyse data streams in real time and facilitate provision of smart solutions designed to provide decision support. Existing IoT based solutions are mainly domain dependent, providing stream processing and analytics focusing on specific areas (smart cities, healthcare etc. In the context of agri food industry, a variety of external parameters belonging to different domains (e.g. weather conditions, regulations etc. have a major influence over the food supply chain, while flexible and adaptive IoT frameworks, essential to truly realize the concept of smart farming, are currently inexistent. In this paper, we propose Agri IoT, a semantic framework for IoT based smart farming applications, which supports reasoning over various heterogeneous sensor data streams in real time. Agri IoT can integrate multiple cross domain data streams, providing a complete semantic processing pipeline, offering a common framework for smart farming applications. Agri IoT supports large scale data analytics and event detection, ensuring seamless interoperability among sensors, services, processes, operations, farmers and other relevant actors, including online information sources and linked open datasets and streams available on the Web.
A large scale web QoS prediction scheme for the Industrial Internet of Things based on a kernel machine learning algorithm
Venue: Comput. Networks

Cloud computing plays an essential role in enabling practical applications based on the Industrial Internet of Things (IIoT) Hence, the quality of these services directly impacts the usability of IIoT applications. To select or recommend the best web and cloud based services, one method is to mine the vast data that are pertinent to the quality of service (QoS) of such services. To enable dynamic discovery and composition of web services, one can use a set of well defined QoS criteria to describe and distinguish functionally similar web services. In general, QoS is a nonfunctional performance index of web services, and it might be user dependent. Hence, to fully assess the QoS of all available web services, a user normally would have to invoke every one of them. This implies that the QoS values for services that the user has not invoked would be missing. If the number of web services available is large, it is virtually inevitable for this to happen because invoking every single service would be prohibitively expensive. This issue is typically resolved by employing some predication algorithms to estimate the missing QoS values. In this paper, a data driven scheme of predicting the missing QoS values for the IIoT based on a kernel least mean square algorithm (KLMS) is proposed. During the data prediction process, the Pearson correlation coefficient (PCC) is initially introduced to find the relevant QoS values from similar service users and web service items for each known QoS entry. Next, KLMS is used to analyze the hidden relationships between all the known QoS data and corresponding QoS data with the highest similarities. We therefore can apply the derived coefficients for the prediction of missing web service QoS values. An extensive performance study based on a public data set is conducted to verify the prediction accuracy of our proposed scheme. This data set includes 200 distributed service users on 500 web service items with a total of 1,858,260 intermediate data values. The experiment results show that our proposed KLMS based prediction scheme has better prediction accuracy than traditional approaches.
Fracture toughness and wear properties of nanosilica/epoxy composites under marine environment

In this research, we report the use of a commercial epoxy based nanocomposite with 2 wt nanosilica to enhance the fracture toughness and wear performance of neat epoxy under marine environment. The mechanical behaviours of neat epoxy and the nanosilica enhanced epoxy composite are characterised after different periods of immersion in sea water (0 day, 7 days and 30 days) The experimental results indicate that sea water immersion does not greatly affect the tensile behaviours of the epoxy or the nanosilica enhanced epoxy nanocomposite. However, the fracture toughness of the neat epoxy is weakened by the sea water immersion with an 18.5% decrease after 7 days immersion and no further decrease after 30 days immersion. The fracture toughness of the nanocomposite also decreases after immersion, but the final value after immersion is comparable to that of the neat epoxy without immersion. The friction coefficient of the neat epoxy increases but that of the nanocomposite decreases with increasing immersion in sea water. The proposed mechanisms are also discussed here.
High frequency stimulation induced peptide release synchronizes arcuate kisspeptin neurons and excites GnRH neurons
Venue: eLife

Kisspeptin (Kiss1) and neurokinin B (NKB) neurocircuits are essential for pubertal development and fertility. Kisspeptin neurons in the hypothalamic arcuate nucleus (Kiss1ARH) co express Kiss1, NKB, dynorphin and glutamate and are postulated to provide an episodic, excitatory drive to gonadotropin releasing hormone 1 (GnRH) neurons, the synaptic mechanisms of which are unknown. We characterized the cellular basis for synchronized Kiss1ARH neuronal activity using optogenetics, whole cell electrophysiology, molecular pharmacology and single cell RT PCR in mice. High frequency photostimulation of Kiss1ARH neurons evoked local release of excitatory (NKB) and inhibitory (dynorphin) neuropeptides, which were found to synchronize the Kiss1ARH neuronal firing. The light evoked synchronous activity caused robust excitation of GnRH neurons by a synaptic mechanism that also involved glutamatergic input to preoptic Kiss1 neurons from Kiss1ARH neurons. We propose that Kiss1ARH neurons play a dual role of driving episodic secretion of GnRH through the differential release of peptide and amino acid neurotransmitters to coordinate reproductive function.
Prefrontal Parvalbumin Neurons in Control of Attention
Venue: Cell

While signatures of attention have been extensively studied in sensory systems, the neural sources and computations responsible for top down control of attention are largely unknown. Using chronic recordings in mice, we found that fast spiking parvalbumin (FS PV) interneurons in medial prefrontal cortex (mPFC) uniformly show increased and sustained firing during goal driven attentional processing, correlating to the level of attention. Elevated activity of FS PV neurons on the timescale of seconds predicted successful execution of behavior. Successful allocation of attention was characterized by strong synchronization of FS PV neurons, increased gamma oscillations, and phase locking of pyramidal firing. Phase locked pyramidal neurons showed gamma phase dependent rate modulation during successful attentional processing. Optogenetic silencing of FS PV neurons deteriorated attentional processing, while optogenetic synchronization of FS PV neurons at gamma frequencies had pro cognitive effects and improved goal directed behavior. FS PV neurons thus act as a functional unit coordinating the activity in the local mPFC circuit during goal driven attentional processing.