nils-herrmann/clean_scirepeval huggingface dataset:
Development of the Biopen a handheld device for surgical printing of adipose stem cells at a chondral wound site

Bioprinting is a process based on additivemanufacturing frommaterials containing living cells. These materials, often referred to as bioink, are based on cytocompatible hydrogel precursor formulations, which gel in amanner compatible with different bioprinting approaches. The bioink properties before, during and after gelation are essential for its printability, comprising such features as achievable structural resolution, shape fidelity and cell survival. However, it is thefinal properties of thematured bioprinted tissue construct that are crucial for the end application. During tissue formation these properties are influenced by the amount of cells present in the construct, their proliferation,migration and interactionwith thematerial. A calibrated computational framework is able to predict the tissue development andmaturation and to optimize the bioprinting input parameters such as the startingmaterial, the initial cell loading and the construct geometry. In this contribution relevant bioink properties are reviewed and discussed on the example ofmost popular bioprinting approaches. The effect of cells on hydrogel processing and vice versa is highlighted. Furthermore, numerical approaches were reviewed and implemented for depicting the cellular mechanics within the hydrogel as well as for prediction ofmechanical properties to achieve the desired hydrogel construct considering cell density, distribution andmaterial cell interaction.
Development of the Biopen a handheld device for surgical printing of adipose stem cells at a chondral wound site

The main goal of this study is to investigate a combination of viscosity sensitive and viscosityinsensitive fluorescent dyes to distinguish different rheological states of hydrogel based biostructural materials and carriers in biological tissues and to assess their corresponding location areas. The research is done in the example of alginate hydrogel stained with viscosity sensitive dyes Seta 470 and Seta 560 as well as the viscosity insensitive dye Seta 650. These dyes absorb/emit at 469/518, 565/591 and 651/670 nm, respectively. The rheological state of the alginate, the area of the fluorescence signal and the mass of the dense alginate versus the calcium gluconate concentration utilized for alginate gelation were studied in vitro. The most pronounced change in the fluorescence signal area was found at the same concentrations of calcium gluconate (below ~1% as the change in the alginate plaque mass. The stained alginate was also implanted in situ in rat hip and myocardium and monitored using fluorescence imaging. In summary, our data indicate that the viscosity sensitive dye in combination with the viscosity insensitive dye allow tracking the biodegradation of the alginate hydrogel and determining the rheological state of hydrogel in biological tissue, which both should have relevance for research and clinical applications. Using this method we estimated the half life of the dense alginate hydrogel in a rat hip to be in the order of 4 d and about 6 8 d in rat myocardium. The half life of the dense hydrogel in the myocardium was found to be long enough to prevent aneurysm rupture of the left ventricle wall, one of the more severe complications of the early post infarction period.
Characterisation and genetic analysis of Mycoplasma hominis and Mycoplasma pneumoniae

Mycoplasmas represent some of the smallest and simplest free living organisms known. Mycoplasma hominis and Mycoplasma pneumoniae are two human pathogens that colonise the urogenital and respiratory tracts, respectively, causing a diverse range of disease. Detection of Mycoplasma hominis is hampered by the fastidious nature and genetic heterogeneity of this organism. Characterisation of mycoplasmas is becoming more important due to increasing antibiotic resistance, particularly in M. pneumoniae, and the need for more discriminatory methods to enhance epidemiology and examine transmission chains. Firstly, this thesis develops a quantitative, multiplex, real time PCR assay to simultaneously detect M. hominis and Ureaplasma species in neonatal clinical specimens, where infection is associated with chronic lung disease, bacteremia and other clinical signs. Results showed that the PCR method was clinically more sensitive than culture and has applications for monitoring bacterial load in clinical specimens and characterising bacterial response to antibiotics. Secondly, genetic characterisation of M. hominis was undertaken by the examination of the variable adherence associated antigen and the development of sequence based typing. Due to the genetic heterogeneity of M. hominis, bioinformatics analysis of genomic sequence was used as a novel method to develop a minimum multi locus sequence typing (MLST) scheme that accurately represented genomic phylogeny of this species. Finally, an MLST scheme was developed for M. pneumoniae, to aid the analysis of epidemic periods and clusters of infection. A successful scheme was developed based on eight housekeeping genes which had increased discrimination of M. pneumoniae compared to established typing methods for this organism. Furthermore, the MLST scheme was found to be representative of genomic sequence derived phylogeny, with two distinct genetic clades identified. Application of this MLST to UK epidemics revealed that no predominant sequence type was responsible for the epidemic periods studied, indicating a polyclonal population, supporting the hypothesis that epidemics are driven by population immunity.
Generating Images from Captions with Attention
Venue: ICLR

Motivated by the recent progress in generative models, we introduce a model that generates images from natural language descriptions. The proposed model iteratively draws patches on a canvas, while attending to the relevant words in the description. After training on Microsoft COCO, we compare our model with several baseline generative models on image generation and retrieval tasks. We demonstrate that our model produces higher quality samples than other approaches and generates images with novel scene compositions corresponding to previously unseen captions in the dataset.
Solar based lemon grass essential oil distillation for sustainability and livelihood in tribal community
Venue: 2016 IEEE Global Humanitarian Technology Conference (GHTC)

Lemon grass essential oil is used in manufacture of soaps, beauty products, and mosquito repellents. Nearly, 40% of world lemon grass oil is produced in India and Kerala state plays a major role. Valaramkunnu is a village in Wayanad district of Kerala, situated on the top of a hill with 300 inhabitants. The villagers walk for 8 km down the hill for daily wages as there is no other source of income. 25 acres of land is available, where lemongrass is grown naturally. The village had a history of extracting lemon grass oil, has two problems a) Batch operation oil extraction is limited by equilibrium and b) Fire wood is used as energy source this results in deforestation and therefore not a sustainable energy source. To address these challenges, a semi continuous lab scale distillation was set up to overcome the limitation of equilibrium and was tested. The proposed system was initially tested at lab scale. A prototype lemon grass essential oil is setup in Valaramkunnu. For the prototype, a solar steam generation system is chosen. Effects of process parameters such as drying time, steam temperature, distillation time and packing density on oil yield were studied. It was found that 8 times more essential oil can be extracted, when compared to existing commercial methodologies. It is also estimated that, nearly 55 litres of oil per acre per annum may be produced in Valaramkunnu. Based on the current price of lemon grass oil, the villagers are estimated to earn INR 800,000 per annum. The report will describe the socioeconomic disadvantages faced by the study population, limitations of their attempts to address these disadvantages, and the analysis to rationalize projected benefits from the proposed technological and social interventions.
[gugjeribyu] jisogganeunggaebalmogpyo(Sustainable Development Goals)wa yangseongpyeongdeung dalseongeul wihan UN Women ataejiyeog samusoyi "SDG gicoseon yeongu

coegeun, gugjesahoeyi gaebalhyeobryeog gwanryeon nonyiga saeceonnyeongaebalmogpyo(Millennium Development Goals, iha MDG)eseo jisogganeunggaebalmogpyo(Sustainable Development Goals, iha SDG)ro ihaenghayeossda. ijeonyi saeceonnyeongaebalmogpyo(MDG)ga 8gae mogpyowa 21gae sebumogpyoro irueojin banmyeon, SDGneun 17gae mogpyowa 169gaeyi sebumogpyoro guseongdoeeo.
Temporal Segment Networks: Towards Good Practices for Deep Action Recognition
Venue: ECCV

Deep convolutional networks have achieved great success for visual recognition in still images. However, for action recognition in videos, the advantage over traditional methods is not so evident. This paper aims to discover the principles to design effective ConvNet architectures for action recognition in videos and learn these models given limited training samples. Our first contribution is temporal segment network (TSN) a novel framework for video based action recognition. which is based on the idea of long range temporal structure modeling. It combines a sparse temporal sampling strategy and video level supervision to enable efficient and effective learning using the whole action video. The other contribution is our study on a series of good practices in learning ConvNets on video data with the help of temporal segment network. Our approach obtains the state the of art performance on the datasets of HMDB51 69.4\ and UCF101 94.2\ We also visualize the learned ConvNet models, which qualitatively demonstrates the effectiveness of temporal segment network and the proposed good practices (Models and code at https:/github.com/yjxiong/temporal segment networks)
Shear behaviors of 'real' natural un matching joints of granite with equivalent joint roughness coefficients

Contact planes of a natural unfilled rock joint often portray dissimilar roughness characteristics particularly at shallow depth. Some researchers investigated shear strength behaviors of un matching joints (i.e. joints with dissimilar surface morphologies) through laboratory experiments using mimicked discontinuities. This study aimed to explore shear behaviors of 'real' natural un matching joints (with similar averaged joint roughness coefficients (JRCs) in the Singhbhum Granite (India) based on laboratory investigations. Direct shear tests were performed on a total of 18 encapsulated jointed samples, split into three groups, under (a) three different low normal stresses 0.70 MPa) with increasing values; (b) three different high normal stresses (within a range of 0.98 1.99 MPa) with increasing values; and (c) one particular intermediate normal stress 0.99 MPa) for five times, where direction of shearing was kept same as the dip direction of the joints in situ. Shear behaviors of the investigated joints portray diverse patterns. Moreover, most of the obtained behavioral patterns look different from the typical shear stress shear displacement graph in the literature that are based on direct shear test results in case of matching rock discontinuities. Influence of surface morphology on shear behavior, shear stress fluctuations with displacement, variation of JRC values with the increase in normal stresses and observations on peak friction angle were critically analyzed. Effect of cycles of shearing on shear strength was also examined. Plausible reasons behind the uniqueness of the results were explained.
Excited State Modulation for Organic Afterglow: Materials and Applications.
Venue: Advanced materials

Organic afterglow materials, developed recently by breaking through the difficulties in modulating ultrafast decayed excited states, exhibit ultralong lived emission for persistent luminescence with lifetimes of several orders of magnitude longer than traditional fluorescent and phosphorescent emissions at room temperature. Their exceptional properties, namely ultralong luminescent lifetime, large Stokes shifts, facile excited state transformation, and environmentally sensitive emission, have led to a diverse range of advanced optoelectronic applications. Here, the organic afterglow is reviewed from the perspective of fundamental concepts on both phenomenon and mechanism, examining the technical challenges in relation to excited state tuning and lifetime elongation. In particular, the advances in material design strategies that afford a large variety of organic afterglow materials for a broad utility in optoelectronics including lighting and displays, anti counterfeiting, optical recording, chemical sensors and bio imaging are highlighted.
Long afterglow metal organic frameworks: reversible guest induced phosphorescence tunability+ +Electronic supplementary information (ESI) available. CCDC 1450104. For ESI and crystallographic data in CIF or other electronic format see DOI: 10.1039/c6sc00563b
Venue: Chemical science

We report that two types of Zn terephthalate (TPA) MOFs (namely [Zn(TPA)(DMF) (1 DMF) and MOF 5) could exhibit an obvious room temperature afterglow emission with a time resolved luminescence lifetime as high as 0.47 seconds.
A systematic review and meta analysis of adjunctive therapies in diabetic foot ulcers.
Venue: Journal of vascular surgery

Multiple adjunctive therapies have been proposed to accelerate wound healing in patients with diabetes and foot ulcers. The aim of this systematic review is to summarize the best available evidence supporting the use of hyperbaric oxygen therapy (HBOT) arterial pump devices, and pharmacologic agents (pentoxifylline, cilostazol, and iloprost) in this setting.  We searched MEDLINE, Embase, Cochrane Central Register of Controlled Trials, Web of Science, and Scopus through October 2011. Pairs of independent reviewers selected studies and extracted data. Predefined outcomes of interest were complete wound healing and amputation.  We identified 18 interventional studies; of which 9 were randomized, enrolling 1526 patients. The risk of bias in the included studies was moderate. In multiple randomized trials, the addition of HBOT to conventional therapy (wound care and offloading) was associated with increased healing rate (Peto odds ratio, 14.25; 95% confidence interval, 7.08 28.68) and reduced major amputation rate (odds ratio, 0.30; 95% confidence interval, 0.10 0.89) compared with conventional therapy alone. In one small trial, arterial pump devices had a favorable effect on complete healing compared with HBOT and in another small trial compared with placebo devices. Neither iloprost nor pentoxifylline had a significant effect on amputation rate compared with conventional therapy. No comparative studies were identified for cilostazol in diabetic foot ulcers.  There is low to moderate quality evidence supporting the use of HBOT as an adjunctive therapy to enhance diabetic foot ulcer healing and potentially prevent amputation. However, there are only sparse data regarding the efficacy of arterial pump devices and pharmacologic interventions.
A Study of LoRa: Long Range Low Power Networks for the Internet of Things
Venue: Sensors

LoRa is a long range, low power, low bitrate, wireless telecommunications system, promoted as an infrastructure solution for the Internet of Things: end devices use LoRa across a single wireless hop to communicate to gateway(s) connected to the Internet and which act as transparent bridges and relay messages between these end devices and a central network server. This paper provides an overview of LoRa and an in depth analysis of its functional components. The physical and data link layer performance is evaluated by field tests and simulations. Based on the analysis and evaluations, some possible solutions for performance enhancements are proposed.
Do LoRa Low Power Wide Area Networks Scale?
Venue: MSWiM

New Internet of Things (IoT) technologies such as Long Range (LoRa) are emerging which enable power efficient wireless communication over very long distances. Devices typically communicate directly to a sink node which removes the need of constructing and maintaining a complex multi hop network. Given the fact that a wide area is covered and that all devices communicate directly to a few sink nodes a large number of nodes have to share the communication medium. LoRa provides for this reason a range of communication options (centre frequency, spreading factor, bandwidth, coding rates) from which a transmitter can choose. Many combination settings are orthogonal and provide simultaneous collision free communications. Nevertheless, there is a limit regarding the number of transmitters a LoRa system can support. In this paper we investigate the capacity limits of LoRa networks. Using experiments we develop models describing LoRa communication behaviour. We use these models to parameterise a LoRa simulation to study scalability. Our experiments show that a typical smart city deployment can support 120 nodes per 3.8 ha, which is not sufficient for future IoT deployments. LoRa networks can scale quite well, however, if they use dynamic communication parameter selection and/or multiple sinks.
Hybrid Garbage Collection for Multi Version Concurrency Control in SAP HANA
Venue: SIGMOD Conference

While multi version concurrency control (MVCC) supports fast and robust performance in in memory, relational databases, it has the potential problem of a growing number of versions over time due to obsolete versions. Although a few TB of main memory is available for enterprise machines, the memory resource should be used carefully for economic and practical reasons. Thus, in order to maintain the necessary number of versions in MVCC, versions which will no longer be used need to be deleted. This process is called garbage collection. MVCC uses the concept of visibility to define garbage. A set of versions for each record is first identified as candidate if their version timestamps are lower than the minimum value of snapshot timestamps of active snapshots in the system. All such candidates, except the one which has the maximum version timestamp, are safely reclaimed as garbage versions. In mixed OLTP and OLAP workloads, the typical garbage collector may not effectively reclaim record versions. In these workloads, OLTP applications generate a high volume of new versions, while long lived queries or transactions in OLAP applications often block garbage collection, since we need to compare the version timestamp of each record version with the snapshot timestamp of the oldest, long lived snapshot. Thus, these workloads typically cause the in memory version space to grow. Additionally, the increasing version chains of records over time may also increase the traversal cost for them. In this paper, we present an efficient and effective garbage collector called HybridGC in SAP HANA. HybridGC integrates three novel concepts of garbage collection: timestamp based group garbage collection, table garbage collection, and interval garbage collection. Through experiments using mixed OLTP and OLAP workloads, we show that HybridGC effectively and efficiently collects garbage versions with negligible overhead.
Quantification winter wheat LAI with HJ 1CCD image features over multiple growing seasons
Venue: Int. J. Appl. Earth Obs. Geoinformation

Remote sensing images are widely used to map leaf area index (LAI) continuously over landscape. The objective of this study is to explore the ideal image features from Chinese HJ 1 A/B CCD images for estimating winter wheat LAI in Beijing. Image features were extracted from such images over four seasons of winter wheat growth, including five vegetation indices (VIs) principal components (PC) tasseled cap transformations (TCT) and texture parameters. The LAI was significantly correlated with the near infrared reflectance band, five VIs [normalized difference vegetation index, enhanced vegetation index (EVI) modified nonlinear vegetation index (MNLI) optimization of soil adjusted vegetation index, and ratio vegetation index] the first principal component (PC1) and the second TCT component (TCT2) However, these image features cannot significantly improve the estimation accuracy of winter wheat LAI in conjunction with eight texture measures. To determine the few ideal features with the best estimation accuracy, partial least squares regression (PLSR) and variable importance in projection (VIP) were applied to predict LAI values. Four remote sensing features (TCT2, PC1, MNLI and EVI) were chosen based on VIP values. The result of leave one out cross validation demonstrated that the PLSR model based on these four features produced better result than the ten features' model, throughout the whole growing season. The results of this study suggest that selecting a few ideal image features is sufficient for LAI estimation.
KOMUNITI PEMBELAJARAN PROFESIONAL APLIKASI DALAM KALANGAN KOMUNITI SMKA DI NEGERI JOHOR

ABSTRAK KomunitiPembelajaran Profesional (KPP) merupakan satu proses penambahbaikan sekolahyang memerlukan kepimpinan sekolah dan komunitinya bekerja secara kolaboratifuntuk meningkatkan kecemerlangan murid. Justeru itu, fokus KPP tertumpu kepadasatu anjakan untuk membudayakan semula konsep pembelajaran dengan memberikanpeluang kepada komuniti sekolah bekerja secara berpasukan, mengutamakan perbincangan, pertambahan ilmu, pertukaran idea dan bahan pengajaran danpembelajaran, mengenalpasti matlamat, visi, misi dan seterusnya mengaturkanpelan tindakan untuk mencapai matlamat yang ditetapkan.Kajian ini bertujuan untuk melihat pelaksanaan atribut atribut KPP dalam kalangan komuniti sekolahdi Sekolah Menengah Kebangsaan Agama (SMKA) Kajian secara mixed method ini melibatkan pengumpulan dan penganalisaan datamelalui kombinasi pendekatan kaedah kuantitatif dan kualitatif melibatkan 139 orang guru dan dua orang pengetua di dua buah SMKA dinegeri Johor. Soal selidik School Professional Staff as Learning CommunityQuestionnaire (Hord, 1996) yang mencatatkan nilai alpha Cronbach 0.9458telah digunakan dalam kajian ini. Prosesanalisis data kajian ini menggunakan pendekatan triangulasi metodologi dan hasilkajian mendapati atribut atribut KPP seperti perkongsian kepimpinan dankepimpinan menyokong, perkongsian misi dan visi, perkongsian amalan personal,pembelajaran secara kolektif dan sokongan organisasi berjaya dilaksanakan dalamkalangan komuniti SMKA. Kata kunci Komuniti PembelajaranProfesional (KPP) Pengajaran dan Pembelajaran (PPTeaching Learning (T&L)