nils-herrmann/clean_scirepeval huggingface dataset:
Palladium coated copper wire — Characteristics and wire behavior in BSOB process and it's reliability performance

The successful introduction of copper wire to semiconductor industry had a significant impact on the manufacturing cost thus copper wire which is 60%-70% cheaper than gold as an interconnecting material between die and lead have become the preferred wire for new devices and conversion status for semiconductor companies indicate that migration from gold to copper wire is a major accomplishment. In addition to this, reliability of devices which could not pass MSL-1 at 260 deg C requirement owing to development of kerkendall voiding (which results from very fast IMC growth rate especially after TC500 cycles) have been overcome. But as compared to quality responses and manufacturability, especially on BSOB wirebond process (Bond-stitch on ball) copper wire had been found out also to be more susceptible to issues like lifted ball, cratering and stitch problems (short tail, lifted stitch) as that of gold wire process. So the cost savings is not justifiable because of quality issues. Most of the issues have been attributed mainly due to the fast oxidation characteristics of the copper wire itself and its free air ball, although newer copper kit designs with nitrogen supply focused on free air ball and bond pad area have been developed, the issues had not been mitigated as wirebonding is still done at elevated temperatures. Studies have been conducted across the industry and most of the solution presented is to coat the copper wire material with Palladium, thus the introduction of CuPd wire (Palladium coated copper wire). A CuPd wire still maintains the electrical characteristics of the copper (lower resistivity than gold, copper core at 99.99%) while palladium as a noble metal prevents oxidation of the copper wire. The wire cost is 2-3 times that of a bare copper but still much cheaper as compared to gold wire. This paper aims to provide the results of studies conducted on a CuPd wire on a DFN package of 0.50mm package thickness which was done in conjunction with bare copper wire utilizing a BSOB process. Study was focused on the free air ball, distribution of palladium after electro flame-off application, bondability for 1st and 2nd bond, oxidation response and reliability tests. The results of studies will show the difference between CuPd wire bare copper wire and why reliability failure was encountered on the bare copper BSOB and not on the CuPd BSOB.
Affordance-feasible planning with manipulator wrench spaces

This work introduces an affordance characterization employing mechanical wrenches as a metric for predicting and planning with workspace affordances. Although affordances are a commonly used high-level paradigm for robotic task-level planning and learning, the literature has been sparse regarding how to characterize the agent in this object-agent-environment framework. In this work, we propose decomposing a behavior into a vocabulary of characteristic requirements and capabilities that are suitable to predict the affordances of various parts of the workspace. Specifically, we investigate mechanical wrenches as a viable representation of these affordance requirements and capabilities. We then use this vocabulary in a planning system to compose complex motions from simple behavior types in continuous space. The utility of the framework for complex planning is demonstrated on example scenarios both in simulation and with real-world industrial manipulators.
Detecting Leg Bone Fracture In X-Ray Images

The image processing techniques are very useful for many applications such as biology, security, satellite imagery, personal photo, medicine, etc. The procedures of image processing such as image enhancement, image segmentation and feature extraction are used for fracture detection system.This paper uses Canny edge detection method for segmentation.Canny method produces perfect information from the bone image. The main aim of this research is to detect human lower leg bone fracture from X-Ray images. The proposed system has three steps, namely, preprocessing, segmentation, and fracture detection. In feature extraction step, this paper uses Hough transform technique for line detection in the image. Feature extraction is the main task of the system. The results from various experiments show that the proposed system is very accurate and efficient.
A Vector Space Model for Automatic Indexing

In a document retrieval, or other pattern matching environment where stored entities (documents) are compared with each other or with incoming patterns (search requests), it appears that the best indexing (property) space is one where each entity lies as far away from the others as possible; in these circumstances the value of an indexing system may be expressible as a function of the density of the object space; in particular, retrieval performance may correlate inversely with space density. An approach based on space density computations is used to choose an optimum indexing vocabulary for a collection of documents. Typical evaluation results are shown, demonstating the usefulness of the model.
Magic moments in situated mediascapes

In this paper, we describe the situation and factors that lead to "Magic Moments" in mediascape experiences and discuss the implications for how to design these magic moments without them appearing contrived. We introduce a framework for Experience Design and describe a set of design heuristics which should extend the field of HCI to encompass aspects of user experience, mobility, the outside environment and facets of the new medium. The distinctive feature of mediascapes is their link to the physical environment. The findings are primarily based on analysis of public reaction to Riot! 1831, a mediascape in the form of an interactive drama which is based on the actual riots that took place in a public square in Bristol, England in 1831.
Marijuana: respiratory tract effects.

Marijuana is the most commonly used drug of abuse in the USA. It is commonly abused through inhalation and therefore has effects on the lung that are similar to tobacco smoke, including increased cough, sputum production, hyperinflation, and upper lobe emphysematous changes. However, at this time, it does not appear that marijuana smoke contributes to the development of chronic obstructive pulmonary disease. Marijuana can have multiple physiologic effects such as tachycardia, peripheral vasodilatation, behavioral and emotional changes, and possible prolonged cognitive impairment. The carcinogenic effects of marijuana are unclear at this time. Studies are mixed on the ability of marijuana smoke to increase the risk for head and neck squamous cell carcinoma, lung cancer, prostate cancer, and cervical cancer. Some studies show that marijuana is protective for development of malignancy. Marijuana smoke has been shown to have an inhibitory effect on the immune system. Components of cannabis are under investigation as treatment for autoimmune diseases and malignancy. As marijuana becomes legalized in many states for medical and recreational use, other forms of tetrahydrocannabinol (THC) have been developed, such as food products and beverages. As most research on marijuana at this time has been on whole marijuana smoke, rather than THC, it is difficult to determine if the currently available data is applicable to these newer products.
Management of juvenile idiopathic arthritis: hitting the target

The treatment of juvenile idiopathic arthritis (JIA) is evolving. The growing number of effective drugs has led to successful treatment and prevention of long-term sequelae in most patients. Although patients with JIA frequently achieve lasting clinical remission, sustained remission off medication is still elusive for most. Treatment approaches vary substantially among paediatric rheumatologists owing to the inherent heterogeneity of JIA and, until recently, to the lack of accepted and well-evidenced guidelines. Furthermore, many pertinent questions related to patient management remain unanswered, in particular regarding treatment targets, and selection, intensity and sequence of initiation or withdrawal of therapy. Existing JIA guidelines and recommendations do not specify treat-to-target or tight control strategies, in contrast to adult rheumatology in which these approaches have been successful. The concepts of window of opportunity (early treatment to improve long-term outcomes) and immunological remission (abrogation of subclinical disease activity) are also fundamental when defining treatment methodologies. This Review explores the application of these concepts to JIA and their possible contribution to the development of future clinical guidelines or consensus treatment protocols. The article also discusses how diverse forms of standardized, guideline-led care and personalized treatment can be combined into a targeted, patient-centred approach to optimize management strategies for patients with JIA.
Orodispersible drug formulations for children and elderly.

Various orodispersible drug formulations have been recently introduced into the market. Oral lyophilisates and orodispersible granules, tablets or films have enriched the therapeutic options. In particular, the paediatric and geriatric population may profit from the advantages like convenient administration, lack of swallowing, ease of use. Until now, only a few novel products made it to the market as the development and production usually is more expensive than for conventional oral drug dosage forms like tablets or capsules. The review reports the recent advances, existing and upcoming products, and the significance of formulating patient-friendly oral dosage forms. The preparation of the medicines can be performed both in pharmaceutical industry and in community pharmacies. Recent advances, e.g. drug printing technologies, may facilitate this process for community or hospital pharmacies. Still, regulatory guidelines and pharmacopoeial monographs lack appropriate methods, specifications and global harmonization to foster the development of innovative orodispersible drug dosage forms.
A Proof of the Block Model Threshold Conjecture

We study a random graph model called the “stochastic block model” in statistics and the “planted partition model” in theoretical computer science. In its simplest form, this is a random graph with two equal-sized classes of vertices, with a within-class edge probability of q and a between-class edge probability of q′. A striking conjecture of Decelle, Krzkala, Moore and Zdeborová [9], based on deep, nonrigorous ideas from statistical physics, gave a precise prediction for the algorithmic threshold of clustering in the sparse planted partition model. In particular, if q = a/n and q′ = b/n, s = (a − b)/2 and d = (a + b)/2 then Decelle et al. conjectured that it is possible to efficiently cluster in a way correlated with the true partition if s > d and impossible if s < d. By comparison, until recently the best-known rigorous result showed that clustering is possible if s > Cd lnd for sufficiently large C. In a previous work, we proved that indeed it is information theoretically impossible to cluster if s ≤ d and moreover that it is information theoretically impossible to even estimate the model parameters from the graph when s < d. Here we prove the rest of the conjecture by providing an efficient algorithm for clustering in a way that is correlated with the true partition when s > d. A different independent proof of the same result was recently obtained by Massoulié [21]. U.C. Berkeley. Supported by NSF grant DMS-1106999, NSF grant CCF 1320105 and DOD ONR grant N000141110140 U.T. Austin and the University of Bonn. Supported by NSF grant DMS-1106999 and DOD ONR grant N000141110140 U.C. Berkeley and the Australian National University. Supported by an Alfred Sloan Fellowship and NSF grant DMS-1208338.
Training Improves Multitasking Performance by Increasing the Speed of Information Processing in Human Prefrontal Cortex

Our ability to multitask is severely limited: task performance deteriorates when we attempt to undertake two or more tasks simultaneously. Remarkably, extensive training can greatly reduce such multitasking costs. While it is not known how training alters the brain to solve the multitasking problem, it likely involves the prefrontal cortex given this brain region's purported role in limiting multitasking performance. Here, we show that the reduction of multitasking interference with training is not achieved by diverting the flow of information processing away from the prefrontal cortex or by segregating prefrontal cells into independent task-specific neuronal ensembles, but rather by increasing the speed of information processing in this brain region, thereby allowing multiple tasks to be processed in rapid succession. These results not only reveal how training leads to efficient multitasking, they also provide a mechanistic account of multitasking limitations, namely the poor speed of information processing in human prefrontal cortex.
SMA bio-robotic mimesis of tendril-based climbing plants: First results

Bio-inspired robots often “come” from the animal world while the plant world has not yet been deeply observed and considered. In this work we addressed a special class of climbing plants, that has evolved to gain height while minimizing the energy expenditure, as a new bio-robotic template: the tendril-bearer plants. These are able to grasp and coil around a support and, after that, push the stem towards the grasped element by recovering a spring-like shape from a wire condition. After the biological analysis, the idea of replicating the grasping by coiling and the pushing by shortening has been focused and replicated by Shape Memory Alloy-based proof of concept prototypes. The results show the feasibility of the approach.
Trajectory generator for autonomous vehicles in urban environments

Nowadays, some developments in the vehicle industry permit a safe and comfortable driving. However, several manufactures and research groups are still working in the improvement of the control strategies and path smoothing algorithms. In this paper, a new trajectory generation approach for autonomous vehicles in urban scenarios, considering parametric equations, is proposed. An algorithm that considers Bezier curves and circumference parametric equations for a real vehicle, specifically in roundabout and urban intersections is presented. This approach is generated in real time and can be adapted to dynamic changes in the route. A smooth trajectory generator computationally efficient and easily implementable is proposed. Moreover, this new trajectory generator reduces the control actions, generated with to a fuzzy controller. Some trials have been performed in an urban circuit with promising performance.
Intelligent plant disease detection system using wireless multimedia sensor networks

Wireless multimedia sensor networks (WMSNs) attracts significant attention in the field of agriculture where disease detection plays an important role. To improve the cultivation yield of plants it is necessary to detect the onset of diseases in plants and provide advice to farmers who will act based on the received suggestion. Due to the limitations of WMSN, it is necessary to design a simple system which can provide higher accuracy with less complexity. In this paper a novel disease detection system (DDS) is proposed to detect and classify the diseases in leaves. Statistical based thresholding strategy is proposed for segmentation which is less complex compared to k-means clustering method. The features extracted from the segmented image will be transmitted through sensor nodes to the monitoring site where the analysis and classification is done using Support Vector Machine classifier. The performance of the proposed DDS has been evaluated in terms of accuracy and is compared with the existing k-means clustering technique. The results show that the proposed method provides an overall accuracy of around 98%. The transmission energy is also analyzed in real time using TelosB nodes.
Acoustic novelty detection with adversarial autoencoders

Novelty detection is the task of recognising events the differ from a model of normality. This paper proposes an acoustic novelty detector based on neural networks trained with an adversarial training strategy. The proposed approach is composed of a feature extraction stage that calculates Log-Mel spectral features from the input signal. Then, an autoencoder network, trained on a corpus of “normal” acoustic signals, is employed to detect whether a segment contains an abnormal event or not. A novelty is detected if the Euclidean distance between the input and the output of the autoencoder exceeds a certain threshold. The innovative contribution of the proposed approach resides in the training procedure of the autoencoder network: instead of using the conventional training procedure that minimises only the Minimum Mean Squared Error loss function, here we adopt an adversarial strategy, where a discriminator network is trained to distinguish between the output of the autoencoder and data sampled from the training corpus. The autoencoder, then, is trained also by using the binary cross-entropy loss calculated at the output of the discriminator network. The performance of the algorithm has been assessed on a corpus derived from the PASCAL CHiME dataset. The results showed that the proposed approach provides a relative performance improvement equal to 0.26% compared to the standard autoencoder. The significance of the improvement has been evaluated with a one-tailed z-test and resulted significant with p < 0.001. The presented approach thus showed promising results on this task and it could be extended as a general training strategy for autoencoders if confirmed by additional experiments.
A Frequency-Division MIMO FMCW Radar System Based on Delta–Sigma Modulated Transmitters

In this paper, we present a hardware-efficient method, which allows to implement multiple-input multiple-output (MIMO) radars with a separation of the transmit (TX) signals in the frequency domain. The proposed architecture uses binary phase-shift keying (BPSK) modulators within the TX paths of a multi-channel frequency-modulated continuous-wave (FMCW) radar. These BPSK modulators are driven by 1-bit sequences, which are generated using ΔΣ-modulators to shift the quantization noise towards high frequencies. Thus, neither multi-bit digital-to-analog converters, nor vector modulators or phase shifters are required for the proposed approach. Since the FMCW principle relies on the evaluation of beat frequencies within a narrow frequency band, the shaped quantization noise is outside the frequencies of interest and can thus be filtered out. The chosen hardware setup is optimized for integration into monolithic microwave integrated circuits (MMICs), which is demonstrated by a prototype system based on 77-GHz chips. Several MMICs are combined to realize a radar frontend with six TX and eight receive channels resulting in 48 MIMO channels. A signal-processing approach is derived and a method to reduce ambiguities is presented. Measurements demonstrate a range resolution of 15 cm and a 3-dB beamwidth of 3 ° with position standard deviations better than 1 mm. Furthermore, a measurement example with a target placed outside the unambiguous range of the radar shows an 8-dB power reduction of the unwanted signal from the target at the ambiguous distance. This improvement is achieved by choosing nonidentical frequency spacings for the TX signals.
Distal Femoral Osteotomy for the Valgus Knee: Medial Closing Wedge Versus Lateral Opening Wedge: A Systematic Review.

(1) To determine the radiographic correction/healing rate, patient-reported outcomes, reoperation rate, and complication rate after distal femoral osteotomy (DFO) for the valgus knee with lateral compartment pathology. (2) To summarize the reported results of medial closing wedge and lateral opening wedge DFO.



We conducted a systematic review of PubMed, MEDLINE, and CINAHL to identify studies reporting outcomes of DFOs for the valgus knee. Keywords included "distal femoral osteotomy," "chondral," "cartilage," "valgus," "joint restoration," "joint preservation," "arthritis," and "gonarthrosis." Two authors first reviewed the articles; our study exclusion criteria were then applied, and the articles were included on the basis relevance defined by the aforementioned criteria. The Methodological Index for Nonrandomized Studies scale judged the quality of the literature. Sixteen studies were relevant to the research questions out of 191 studies identified by the original search.



Sixteen studies were identified reporting on 372 osteotomies with mean follow-up of 45 to 180 months. All studies reported mean radiographic correction to a near neutral mechanical axis, with 3.2% nonunion and 3.8% delayed union rates. There was a 9% complication rate and a 34% reoperation rate, of which 15% were converted to arthroplasty. There were similar results reported for medial closing wedge and lateral opening wedge techniques, with a higher conversion to arthroplasty in the medial closing wedge that was confounded by longer mean follow-up in this group (mean follow-up 100 v 58 months).



DFOs for the valgus knee with lateral compartment disease provide improvements in patient-reported knee health-related quality of life at midterm follow-up but have high rates of reoperation. No evidence exists proving better results of either the lateral opening wedge or medial closing wedge techniques.
Towards an Evaluation of Denoising Algorithms with Respect to Realistic Camera Noise

The development and tuning of denoising algorithms is usually based on readily processed test images that are artificially degraded with additive white Gaussian noise (AWGN). While AWGN allows us to easily generate test data in a repeatable manner, it does not reflect the noise characteristics in a real digital camera. Realistic camera noise is signal-dependent and spatially correlated due to the demosaicking step required to obtain full-color images. Hence, the noise characteristic is fundamentally different from AWGN. Using such unrealistic data to test, optimize and compare denoising algorithms may lead to incorrect parameter tuning or sub optimal choices in research on denoising algorithms. In this paper, we therefore propose an approach to evaluate denoising algorithms with respect to realistic camera noise: we describe a new camera noise model that includes the full processing chain of a single sensor camera. We determine the visual quality of noisy and denoised test sequences using a subjective test with 18 participants. We show that the noise characteristics have a significant effect on visual quality. Quality metrics, which are required to compare denoising results, are applied, and we evaluate the performance of 10 full-reference metrics and one no-reference metric with our realistic test data. We conclude that a more realistic noise model should be used in future research to improve the quality estimation of digital images and videos and to improve the research on denoising algorithms.
The RAM network in pathogenic fungi.

The regulation of Ace2 and morphogenesis (RAM) network is a protein kinase signaling pathway conserved among eukaryotes from yeasts to humans. Among fungi, the RAM network has been most extensively studied in the model yeast Saccharomyces cerevisiae and has been shown to regulate a range of cellular processes, including daughter cell-specific gene expression, cell cycle regulation, cell separation, mating, polarized growth, maintenance of cell wall integrity, and stress signaling. Increasing numbers of recent studies on the role of the RAM network in pathogenic fungal species have revealed that this network also plays an important role in the biology and pathogenesis of these organisms. In addition to providing a brief overview of the RAM network in S. cerevisiae, we summarize recent developments in the understanding of RAM network function in the human fungal pathogens Candida albicans, Candida glabrata, Cryptococcus neoformans, Aspergillus fumigatus, and Pneumocystis spp.