nils-herrmann/clean_scirepeval huggingface dataset:
Streamlining scenario analysis and optimization of key choices in value chains using a modular LCA approach
Venue: The International Journal of Life Cycle Assessment

PurposeThe environmental performance of products or services is often a result of a number of key decisions that shape their life cycles (e.g. techology choices) This paper introduces a modular LCA approach that is capable of reducing the effort involved in performing scenario analyses and optimization when several key choices along a product's value chain lead to many alternative life cycles.MethodsThe main idea is that the value chain of a product can be divided into interconnected but exchangeable modules, which together represent a full life cycle. A module is comprised of unit processes from the practitioner's LCI database. The inputs, outputs, and system boundaries of each module can be tailored to the context of the studied system. Alternatives arise whenever multiple modules produce substitutable products. Unlike in conventional LCI databases, no copies are necessary to represent the same process with different inputs. A module product matrix is used to store this information. It can be used as a basis for an automated scenario analysis of all alternatives or as an input to an optimization model.Results and discussionOur approach is illustrated in two case studies: (1) Passenger car fuel choices are modeled by 15 modules representing 33 alternative value chains for diesel, petrol, natural gas and electric cars. The automated comparison of LCA results indicates that electric mobility is often the preferable option from a climate perspective, but impacts depend strongly on the electricity source. (2) A dynamic optimization model including stocks is built from eight modules to analyze the optimal use of wood for material and energy applications. Results indicate that although direct substitution benefits are higher for energy applications, cascading use of wood can maximize environmental performance over the entire life cycle.ConclusionsThe modular LCA approach permits an efficient modeling and comparison of alternative product life cycles, enabling practitioners to focus on key decisions. It can be applied to exploit a potential that is hidden in LCI databases, which is that they contain many specific inventories but not all useful combinations in the context of scenario analyses. The user defined level of abstraction that is introduced through modules can be helpful in the communication of LCA results. The modular approach also facilitates the integration of LCA and optimization as well as other industrial ecology methods. An open source software is provided to enable others to apply and further develop our implementation of a modular LCA approach.
Apophysitis of the Tibial Tuberosity (Osgood Schlatter Disease) A Review
Venue: Cureus

Osgood Schlatter disease (OSD) is a condition in which the patellar tendon insertion on the tibial tuberosity becomes inflamed. It is a well known condition in late childhood characterized by pain and a bony prominence over the tibial tuberosity. The pain is usually exacerbated by physical activities like running, jumping, and climbing stairs. In the acute stage, the margins of the patellar tendon become blurred in radiographs due to the soft tissue swelling. After three to four months, bone fragmentation at the tibial tuberosity is viewed. In the sub acute stage, soft tissue swelling resolves, but the bony ossicle remains. In the chronic stage, the bone fragment may fuse with the tibial tuberosity which can appear normal. The primary goal in the treatment of OSD is the reduction of pain and swelling over the tibial tuberosity. The patient should limit physical activities until the symptoms are resolved. In some cases, the patient should restrict physical activities for several months. The presence of pain with kneeling because of an ossicle that does not respond to conservative measures is the indication for surgery. In these cases, the removal of the ossicle, surrounding bursa, and the bony prominence is the treatment of choice.
Results of arthroscopic treatment in unresolved Osgood Schlatter disease in athletes
Venue: International Orthopaedics

this study we aimed to determine outcomes following arthroscopic ossicle excision in athletes with unresolved Osgood Schlatter disease (OSD).MethodArthroscopy was performed on 11 patients (11 knees) with OSD between September 2008 and November 2014. Surgical treatment inclusion criteria were determined as: failure of conservative treatment; isolated pain over the tibial tubercle and distal patellar tendon; pain limiting sporting performance at a competitive level. All patients had a documented history of OSD; the mean duration of persistent pain over the tibial tubercle was 15.5 months. The mean age was 23 years. The mean follow up period was 66.1 months.ResultsThe mean latency in returning to sports related training activities after the surgery was 6.7 weeks. The mean Kujala patello femoral score improved from 82.9 points pre operatively, to 98.5 points at the final follow up (p 0.01) The mean Lysholm knee scale score was 87.5 points in the pre operative period, increasing to a score of 96.9 points at final follow up (p 0.01) The mean Tegner activity level score was 7.5 in the pre operative period, increasing to 8.5 post operatively (p 0.01).DiscussionWe investigated the functional outcomes after arthroscopic treatment of unresolved OSD in athletes. All athletes with OSD showed satisfactory functional recovery following arthroscopic treatment. All patients were able to return to the same level of athletic activity.ConclusionArthroscopic surgery for unresolved OSD has the major advantage of faster recovery and avoiding damage to the patellar tendon.
Evidence for light controlled migration amplitude of a sound scattering layer in the Norwegian Sea

The oceanic sound scattering layer (SL) is an ubiquitous acoustic signature of meso pelagic fishes and invertebrates that are important food sources for the oceanic macrofauna and players in the biological carbon pump. We investigated the relationship between SL migration amplitude and light in the Norwegian Sea. Incoming surface irradiance was measured continu ously during night and day. The increasing latitude of the cruise track facilitated a field experi ment wherein night light increased 2 to 3 orders of magnitude during the study period. Concur rent with increased night light, the diel vertical migration amplitude of the SL decreased several hundred meters. The variations in irradiance at the sea surface spanned 6 orders of magnitude during the study period, while the ambient irradiance of the SL mean depth was relatively con stant during both day and nighttime. For the deepest penetrating wavelength (486 nm) the average ambient light was estimated to be 2 x 10 6 mW m 2 nm 1 which corresponded to a total irradiance of 1.9 x 10 7 umol quanta m 2 s 1 The observed variation in migration amplitude is consistent with a behavior whereby the SL organisms keep their ambient light intensities within a particular range. We also observed that SL total backscattering, a proxy for biomass, decreased along with the decrease in migration amplitude. We speculate whether this decrease might, in part, relate to a previously proposed 'photoperiod constraint hypothesis' suggesting that high night light intensities in summer at high latitudes limit options for safe foraging in upper layers at night.
Mapping the talent pool: An exploratory social network analysis of the Southeastern Pennsylvania public school superintendent labor market

.1 I.  Need for the Study .9  Definition of Terms..19 II.  Tracing a Possible Echo Chamber in the Superintendent Shortage Research Studies .22 New Identities for the 21 Century Superintendent Arena .30 Persistent Challenges to the 21 Century Superintendent: The Inequality of Race and Gender .36 Superintendents and School Board Barriers .40 The Superintendent Paradox: Commitment and Job Satisfaction..44 Tapping the "Oughtabes" and the Need for Revised Preparation Programs .48 Summary .54 III.  Overview of Study Design: Instruments and Procedures: Strand 1Bibliometric Analysis and Echo Chamber Effect .58 Overview of Study Design: Instrument and Procedures: Strand 2 Exploratory Analysis of the Superintendent Labor Market Using Social Network Analysis (SNA) .60 Population .64 Validity .65
Comparison of beam generation techniques using a phase only spatial light modulator.
Venue: Optics express

Whether in art or for QR codes, images have proven to be both powerful and efficient carriers of information. Spatial light modulators allow an unprecedented level of control over the generation of optical fields by using digital holograms. There is no unique way of obtaining a desired light pattern however, leaving many competing methods for hologram generation. In this paper, we test six hologram generation techniques in the creation of a variety of modes as well as a photographic image: rating the methods according to obtained mode quality and power. All techniques compensate for a non uniform mode profile of the input laser and incorporate amplitude scaling. We find that all methods perform well and stress the importance of appropriate spatial filtering. We expect these results to be of interest to those working in the contexts of microscopy, optical trapping or quantum image creation.
Arbitrary shaping of on axis amplitude of femtosecond Bessel beams with a single phase only spatial light modulator.
Venue: Optics express

Arbitrary shaping of the on axis intensity of Bessel beams requires spatial modulation of both amplitude and phase. We develop a non iterative direct space beam shaping method to generate Bessel beams with high energy throughput from direct space with a single phase only spatial light modulator. For this purpose, we generalize the approach of Bolduc et al. to non uniform input beams. We point out the physical limitations imposed on the on axis intensity profile for unidirectional beams. Analytical, numerical and experimental results are provided.
All optical spatial light modulator for reconfigurable silicon photonic circuits

Reconfigurable photonic devices capable of routing the flow of light enable flexible integrated optic circuits that are not hardwired but can be externally controlled. Analogous to free space spatial light modulators, we demonstrate all optical wavefront shaping in integrated silicon on insulator photonic devices by modifying the spatial refractive index profile of the device employing ultraviolet pulsed laser excitation. Applying appropriate excitation patterns grants us full control over the optical transfer function of telecommunication wavelength light traveling through the device, thus allowing us to redefine its functionalities. As a proof of concept, we experimentally demonstrate the routing of light between the ports of a multimode interference power splitter with more than 97% total efficiency and negligible losses. Wavefront shaping in integrated photonic circuits provides a conceptually new approach toward achieving highly adaptable and field programmable photonic circuits with applications in optical testing and data communication.
A New Conceptualization and Approach to Learning and Teaching Motivational Interviewing

The purpose of this article is to describe three innovations: 1) the development of traditional motivational interviewing within substance abuse counseling; 2) our development of a new conceptual approach to motivational interviewing in health care; and 3) our development of an eight hour e learning program to teach this approach to motivational interviewing in a more accessible, affordable and standardized format. The progression of the article is as follows: 1) we briefly describe the development of motivational interviewing (MI) and its impact on health behavior change (assuming the reader has had some exposure to motivational interviewing concepts) 2) we describe how and why we have reformulated Miller's original approach to MI to fit the training and needs of health care professionals (HCPs) and 3) we describe the thinking and reasoning that went into the development of an eight hour MI e learning program. Our overarching purpose is to describe how we came to formulate our approach to motivational interviewing in health care based on 25 years of teaching MI using both traditional approaches to MI and our new approach. The reader is referred to our book, Motivational Interviewing for Health Care Professionals: A Sensible Approach 1 for further elaboration of these concepts and their evolution in health care.
Changes in Physical Therapist Students' Self Efficacy for Physical Activity Counseling Following a Motivational Interviewing Learning Module

Healthy People 2020 articulates the need for health professionals to incorporate health promotion counseling into their treatment programs to address personal behaviors that contribute to morbidity and premature mortality, such as smoking, insufficient physical activity, and poor diet. Physical therapists (PTs) have a unique opportunity to discuss health behaviors with their patients during treatment sessions. However, PTs have shown reluctance to engage in health promotion counseling due to a lack of confidence and inadequate training in counseling skills. Motivational interviewing (MI) is a patient centered counseling approach that has been shown to be both efficient and effective in supporting behavior change. The purpose of this case report was to determine if a 4 hour MI learning module increased PT student self efficacy for counseling patients to increase their level of physical activity.  Twenty eight thirdyear doctor of physical therapy students received 4 hours of instruction in MI. The learning module included lecture, video demonstrations, class discussions, student role playing, and practice with standardized patients. Prior to and following the module, students completed a self efficacy questionnaire that measured their level of confidence in counseling patients in the area of physical activity. The students also completed an evaluation of the module.  Students had increased levels of self efficacy for counseling patients to increase their level of physical activity following the learning module (P .001) Furthermore, the majority of students (93% reported they were more likely to discuss physical activity with their patients.  A 4 hour MI learning module increased PT students' self efficacy for counseling patients in the area of physical activity. Future research should examine the students' competence in the technique and whether PT students engage in more health behavior counseling in the clinical setting as a result of this training.
The Role of Motivational Interviewing in Depression and Psychological Well Being in Mothers of Students Having Learning Disabilities

The effects of motivational interviewing on the minimising of depression symptoms and improvement of psychological well being among mothers of students having learning disabilities were studied. The methodology was based on the comparison of pretest posttest Vs control groups. The statistical data included all mothers of primary school students having learning disabilities (50 subjects) and normal students (50 subjects) residing in the city of Ardabil, Iran. Subject selections were made through simple random sampling method and group counselling sessions focused on motivational interviewing were held for the experimental group for total eight "60 minute sessions" The structure of the motivational interviewing sessions was extracted from a prescribed prescript of group therapy. To tabulate the data; Ryff's Scales of Psychological Well Being, Beck Depression Inventory, and Colorado Learning Diff iculties Questionnaire were used. As per the statistical analysis the motivational interviewing can reduce depression symptoms and improve psychological wellbeing in mothers of students having learning disabilities.
Efficient 3D dental identification via signed feature histogram and learning keypoint detection
Venue: Pattern Recognit.

Current methods of dental identification are mainly based on 2D dental radiographs which suffer from speed and accuracy limitations. In this paper, we present an efficient dental identification approach based on 3D dental models. We propose a novel shape descriptor, the Signed Feature Histogram (SFH) which is highly discriminative and can be easily computed to describe the local surface. Based on the SFH, a learning keypoint detection method is adopted to accurately detect the desired keypoints on both antemortem (AM) and postmortem (PM) models. For a given PM model, the optimal initial alignment to the AM model to be matched can be found efficiently and robustly by matching the SFHs between the keypoints. The final matching score is obtained by running the iterative closest point algorithm which further refines the initial alignment. We have performed comparative experiments for the SFH on a public dataset, and state of the art performance is achieved. We also test the identification method on a database of 200 AM models and tested the performance of the proposed approach on 3 different PM datasets comprising complete, incomplete and single tooth models respectively. The experimental results show that both high accuracy and efficiency are achieved with 100% Rank 1 identification accuracy on both complete and incomplete PM models and 74% Rank 1 accuracy on single tooth PM models. The running time is only 300s on average which is about 80times faster than many 2D methods which can take several hours to identify one subject. HighlightsWe use a machine learning method to accurately detect keypoints on dental models.A novel local shape descriptor is proposed which can be efficiently computed.A highly efficient and robust dental identification algorithm is proposed.The proposed method is about 80 times faster than traditional 2D based methods.Promising results are achieved for single tooth identification.
Fast, Exact and Multi scale Inference for Semantic Image Segmentation with Deep Gaussian CRFs
Venue: ECCV

In this work we propose a structured prediction technique that combines the virtues of Gaussian Conditional Random Fields (G CRF) with Deep Learning: (a) our structured prediction task has a unique global optimum that is obtained exactly from the solution of a linear system (b) the gradients of our model parameters are analytically computed using closed form expressions, in contrast to the memory demanding contemporary deep structured prediction approaches [1, 2] that rely on back propagation through time, (c) our pairwise terms do not have to be simple hand crafted expressions, as in the line of works building on the DenseCRF [1, 3] but can rather be 'discovered' from data through deep architectures, and (d) out system can trained in an end to end manner. Building on standard tools from numerical analysis we develop very efficient algorithms for inference and learning, as well as a customized technique adapted to the semantic segmentation task. This efficiency allows us to explore more sophisticated architectures for structured prediction in deep learning: we introduce multi resolution architectures to couple information across scales in a joint optimization framework, yielding systematic improvements. We demonstrate the utility of our approach on the challenging VOC PASCAL 2012 image segmentation benchmark, showing substantial improvements over strong baselines. We make all of our code and experiments available at https:/github.com/siddharthachandra/gcrf.
FASCINATE: Fast Cross Layer Dependency Inference on Multi layered Networks
Venue: KDD

Multi layered networks have recently emerged as a new network model, which naturally finds itself in many high impact application domains, ranging from critical inter dependent infrastructure networks, biological systems, organization level collaborations, to cross platform e commerce, etc. Cross layer dependency, which describes the dependencies or the associations between nodes across different layers/networks, often plays a central role in many data mining tasks on such multi layered networks. Yet, it remains a daunting task to accurately know the cross layer dependency a prior. In this paper, we address the problem of inferring the missing cross layer dependencies on multi layered networks. The key idea behind our method is to view it as a collective collaborative filtering problem. By formulating the problem into a regularized optimization model, we propose an effective algorithm to find the local optima with linear complexity. Furthermore, we derive an online algorithm to accommodate newly arrived nodes, whose complexity is just linear wrt the size of the neighborhood of the new node. We perform extensive empirical evaluations to demonstrate the effectiveness and the efficiency of the proposed methods.
Beyond East vs. West: social class, region, and religion as forms of culture.
Venue: Current opinion in psychology

In this article we seek to further broaden the focus of the psychological study of cultural differences beyond the predominant focus on ethnicity and nationality. We highlight ways that other forms of culture, including social class, region, and religion, sometimes have psychological consequences that parallel those of ethnicity and nationality, and are sometimes more unique. For example, we review recent work that working class culture is more interdependent, holistic, empathic, and vigilant; that regional cultures vary in honor, individualism, conformity, and tightness looseness; and that religions differ in attributions, cognition, working styles, and the bases of morality. We conclude with some recommendations for future work on culture, including the origins of cultures, the multiple forms of culture, the uniqueness and similarities of cultures, and how multiple forms of culture interact.
The Antecedents of Interactive Loyalty

Brand loyalty towards video game consoles may have several antecedents. Gender, genre of video games and network externality may impact brand loyalty, mediated by perceptions of video game console brand personalities. This study investigated these relationships by conducting a principal component factor analysis and testing a structural equation model. The seventh generation of video game consoles was selected as the focal concept. The video game consoles examined included Nintendo's Wii, Microsoft's XBOX 360 and Sony's PlayStation 3. The findings suggest that consumers perceive all video game consoles as competent in nature, and that genre has a tremendous impact upon brand loyalty, perceptions of brand personality as well as network externality. For brand managers and industry practitioners, this study provides demonstrates which variables may influence how consumers create brand personalities of video game consoles and cultivate loyalty toward them. This also furthers and introduces the concept of brand relationship theory into the video game industry.