nils-herrmann/clean_scirepeval huggingface dataset:
Clustering Big Spatiotemporal Interval Data
Venue: IEEE Transactions on Big Data

We propose a model for clustering data with spatiotemporal intervals. This model is used to effectively evaluate clusters of spatiotemporal interval data. A new energy function is used to measure similarity and balance between clusters in spatial and temporal dimensions. We employ as a case study a large collection of parking data from a real CBD area. The proposed model is applied to existing traditional algorithms to address spatiotemporal interval data clustering problem. Results from traditional clustering algorithms are compared and analysed using the proposed energy function.
Point of Interest Recommendations: Learning Potential Check ins from Friends
Venue: KDD

The emergence of Location based Social Network (LBSN) services provides a wonderful opportunity to build personalized Point of Interest (POI) recommender systems. Although a personalized POI recommender system can significantly facilitate users' outdoor activities, it faces many challenging problems, such as the hardness to model user's POI decision making process and the difficulty to address data sparsity and user/location cold start problem. To cope with these challenges, we define three types of friends (i.e. social friends, location friends, and neighboring friends) in LBSN, and develop a two step framework to leverage the information of friends to improve POI recommendation accuracy and address cold start problem. Specifically, we first propose to learn a set of potential locations that each individual's friends have checked in before and this individual is most interested in. Then we incorporate three types of check ins (i.e. observed check ins, potential check ins and other unobserved check ins) into matrix factorization model using two different loss functions (i.e. the square error based loss and the ranking error based loss) To evaluate the proposed model, we conduct extensive experiments with many state of the art baseline methods and evaluation metrics on two real world data sets. The experimental results demonstrate the effectiveness of our methods.
Point of interest recommendations in location based social networks
Venue: SIGSPACIAL

Location based social networks (LBSNs) e.g. Foursquare, Gowalla and Yelp, bridge the physical world with the virtual online world. LBSNs have accumulated plenty of community contributed data such as social links between users, check ins of users on points of interest (POIs) geographical information and categories of POIs, which reflect the preferences of users to POIs. Recommending users with their preferred POIs benefits people to explore new places and businesses to discover potential customers. This paper aims to recommend personalized POIs for users based on their preferences that are learned from the community contributed data. To this end, this paper models the social, categorical, geographical, sequential, and temporal influences on the visiting preferences of users to POIs.
Thermal tolerance and survival responses to scenarios of experimental climatic change: changing thermal variability reduces the heat and cold tolerance in a fly
Venue: Journal of Comparative Physiology B

Climate change poses one of the greatest threats to biodiversity. Most analyses of the impacts have focused on changes in mean temperature, but increasing variance will also impact organisms and populations. We assessed the combined effects of the mean and the variance of temperature on thermal tolerances i.e. critical thermal maxima, critical thermal minima, scope of thermal tolerance, and survival in Drosophilamelanogaster. Our six experimental climatic scenarios were: constant mean with zero variance or constant variance or increasing variance; changing mean with zero variance or constant variance or increasing variance. Our key result was that environments with changing thermal variance reduce the scope of thermal tolerance and survival. Heat tolerance seems to be conserved, but cold tolerance decreases significantly with mean low as well as changing environmental temperatures. Flies acclimated to scenarios of changing variance with either constant or changing mean temperatures exhibited significantly lower survival rate. Our results imply that changing and constant variances would be just as important in future scenarios of climate change under greenhouse warming as increases in mean annual temperature. To develop more realistic predictions about the biological impacts of climate change, such interactions between the mean and variance of environmental temperature should be considered.
Climatic change controls productivity variation in global grasslands
Venue: Scientific reports

Detection and identification of the impacts of climate change on ecosystems have been core issues in climate change research in recent years. In this study, we compared average annual values of the normalized difference vegetation index (NDVI) with theoretical net primary productivity (NPP) values based on temperature and precipitation to determine the effect of historic climate change on global grassland productivity from 1982 to 2011. Comparison of trends in actual productivity (NDVI) with climate induced potential productivity showed that the trends in average productivity in nearly 40% of global grassland areas have been significantly affected by climate change. The contribution of climate change to variability in grassland productivity was 15.2 71.2% during 1982 2011. Climate change contributed significantly to long term trends in grassland productivity mainly in North America, central Eurasia, central Africa, and Oceania; these regions will be more sensitive to future climate change impacts. The impacts of climate change on variability in grassland productivity were greater in the Western Hemisphere than the Eastern Hemisphere. Confirmation of the observed trends requires long term controlled experiments and multi model ensembles to reduce uncertainties and explain mechanisms.
Manfaat Terapi Pijat pada Konstipasi Kronis Anak

Latar belakang. Konstipasi sering ditemukan pada anak dan menimbulkan masalah sosial maupun psikologi. Data menunjukkan 95% kasus konstipasi anak merupakan konstipasi fungsional. Penelitian memperlihatkan dampak yang baik dari terapi pijat yang dihubungkan dengan berbagai kondisi dan penyakit pada anak. Tujuan Melihat implikasi klinis terapi pijat terhadap pasien konstipasi kronis pada anak. Metode. Penelitian prospektif intervensional dilakukan dengan randomisasi dan menggunakan kontrol, terhadap kasus konstipasi berusia 2 14 tahun di Divisi Gastroenterologi Departemen Ilmu Kesehatan Anak RSUPN Cipto Mangunkusumo sejak bulan Februari hingga Juni 2006. Hasil. Jumlah subyek penelitian 16 orang terdiri dari 7/16 laki laki dan 9/16 perempuan. Rerata umur subyek 4,1 tahun (SB=+1,3) Frekuensi buang air besar (b.a.b) pasien konstipasi fungsional mengalami peningkatan setelah diberikan terapi pijat. Jumlah pasien yang mengalami kicipirit, dengan tinja keras berkurang lebih banyak pada kelompok perlakuan dibandingkan kelompok kontrol. Jarak terlama antara b.a.b kelompok perlakuan mengalami penurunan yang lebih besar (6,7+3,2 hari menjadi 3,7+1,7 hari) dibandingkan kelompok kontrol (5,2+2,4 hari menjadi 3,3+1,0 hari) Lama waktu b.a.b kelompok perlakuan berkurang lebih banyak (21,2+18,2 menit menjadi 14,37+8,6 menit) dibandingkan kelompok kontrol (15,6+9,4 menit menjadi 11,8+9,2 menit) Waktu yang dibutuhkan untuk terjadi perbaikan terhadap konstipasi kelompok perlakuan lebih singkat (29,2+24,9 hari) dibandingkan kelompok kontrol (32,2+20,8 hari) Kesimpulan. Terapi pijat dapat membantu mempercepat perbaikan konstipasi kronis fungsional
Oil price volatility forecast with mixture memory GARCH

We expand the literature of volatility and Value at Risk forecasting of oil price returns by comparing the recently proposed Mixture Memory GARCH (MMGARCH) model to other discrete volatility models (GARCH, RiskMetrics, EGARCH, APARCH, FIGARCH, HYGARCH, and FIAPARCH) We incorporate an Expectation Maximization algorithm for parameter estimation of the MMGARCH and find different structures in volatility level as well as shock persistence. MMGARCH is also able to cover asymmetric and long memory effects. Furthermore, a dissimilar memory structure in variance of WTI and Brent crude oil prices is observed which is supported by additional tests. Parameter estimation and comparison of the models reveal significant long memory and asymmetry in oil price returns. In regard of variance forecasting and Value at Risk prediction, it is shown that MMGARCH outperforms the aforementioned models due to its dynamic approach in varying the volatility level and memory of the process. We find MMGARCH superior for application in risk management as a result of its flexibility in adjusting to variance shifts and shocks.
Oil Price Volatility Forecast with Mixture Memory GARCH

First Version: 03/11/2015  We expand the literature of volatility and Value at Risk forecasting of oil price returns by comparing the recently proposed Mixture Memory GARCH (MMGARCH) model to other discrete volatility models (GARCH, FIGARCH, and HYGARCH) We incorporate an Expectation Maximization algorithm for parameter estimation of the MMGARCH and find regimes that differ in volatility level as well as shock persistence. Furthermore, we observe dissimilar memory structure in variance of WTI and Brent crude oil prices which is confirmed by altering the mixture components. In regard of variance forecasting and Value at Risk prediction, we show that MMGARCH outperforms the aforementioned models due to its dynamic approach in varying the volatility level and memory of the process. We find MMGARCH superior for application in risk management as a result of its flexibility in adjusting to variance shifts and shocks.
Hepatorenales Syndrom bei dekompensierter Leberzirrhose
Venue: Medizinische Klinik Intensivmedizin und Notfallmedizin

ZusammenfassungDas Auftreten einer akuten Niereninsuffizienz (AKI) ist eine haufige Komplikation bei Patienten mit fortgeschrittener Leberzirrhose. Als Ursache kommen vorwiegend intrarenale und prarenale Ursachen infrage, wobei bereits geringgradige Veranderungen der Nierenfunktion mit einer Verschlechterung der Prognose einhergehen. Fruhzeitige Massnahmen zur Verbesserung der Nierenfunktion konnen die Prognose deutlich verbessern. Das hepatorenale Syndrom (HRS) ist eine besondere Form der akuten prarenalen Niereninsuffizienz und durch einen Anstieg des Serumkreatinins 1,5 mg/dl charakterisiert. Das HRS ist ein funktionelles Nierenversagen, das durch eine Volumentherapie nicht mehr gebessert werden kann. Es geht mit einer sehr schlechten Prognose einher. Die effektivste Therapie des HRS besteht in der Verabreichung von Terlipressin in Kombination mit Albumin. Damit kann bei etwa 30 50 der Patienten eine Normalisierung der Nierenfunktion erzielt werden. Die Langzeitprognose ist von der Leberfunktion abhangig. Die einzig effektive Langzeittherapie nach Beherrschung der Niereninsuffizienz ist die Lebertransplantation. Kann vor der Transplantation die Nierenfunktion verbessert werden, wird das Uberleben nach der Transplantation signifikant gebessert.AbstractRenal failure is a serious complication in patients with advanced cirrhosis. It occurs in about 20 of patients hospitalized with cirrhosis. In about 70 it is caused by prerenal failure, and in 30 it is due to intrarenal causes. In about 70 of patients with rperenal failure, renal function can be restored with fluid replacement, but the remaining 30 are unresponsive to volume expansion. Minor increase in serum creatinine have been shown to be clinically relevant and can adversely affect survival. Therefore early efforts should be made to avoid precipitation of renal failure.Hepatorenal syndrome (HRS) is a fully reversible impairment of renal function in patients with cirrhosis unresponsive to volume expansion characterized by an acute progressive decrease in kidney function (serumcreatinin 1,5 mg/dl) type 1 HRS, whereas type 2 HRS features a decrease in kidney function over a long time, mostly in patients with refractory ascites. Therapy with vasoconstrictors like terlipressin to reverse splanchnic vasodilation, together with albumin is effective in 30 50 of patients with HRS 1 and improves survival. The only effective longterm therapy is livertransplantation. An improvement of kidney fuction before transplantation is associated with a better outcome and posttransplant kidney function.
The Impact of Contingency Fees on Collective Antitrust Actions: Experiments from Lithuania and Poland

Contingency fee agreements are one if not the only tool that can be used to ensure that small stakes collective antitrust actions are heard, yet they are subject to strong resistance from the European Union. There is a concern that contingency fees could lead to abuses of the system or conflicts of interest, as has been seen in the United States. Contrary to EU policy, two proactive member states Lithuania and Poland have introduced the possibility of using contingency fees in group litigation in order to facilitate group actions. Despite having a lot of potential, this paper will demonstrate that the introduction alone of contingency fees will not facilitate the compensation objective that is embedded in the Directive on damages actions. In addition, it will show that the safeguard policy against frivolous litigation is sufficient to limit the possibilities for litigation abuses, but it is ineffective for monitoring the individual behavior of group representatives.
The activity and use of zinc in poultry diets

Zinc (Zn) is an important nutrient in poultry and its deficiency has been linked with various disorders, in addition to depressed growth and performance. It is now recognised that Zn has a major role in antioxidation, growth and development, production, immunity and stress related issues. Supplementation of Zn can improve growth, augment immunity, enhance antioxidant capacity, increase endocrine secretion and interact with other minerals in the gut. In this review, some of the basic information regarding the importance and activity of Zn within the body and the addition of Zn in poultry diets is discussed.
Recent advances in role of chromium and its antioxidant combinations in poultry nutrition: A review
Venue: Veterinary world

Poultry is reared in open side houses in most of the tropical countries, which results in huge temperature variation in shed causing stress resulting in increased demand of antioxidant supplementation. Since cooling of poultry houses or environment control is very expensive, thus methods focused on nutritional modifications appears to be the much logical approach. Stress increases mineral and vitamin mobilization from tissues and their excretion. Effect of some minerals and vitamin supplements such as chromium (Cr) and ascorbic acid to elevate the negative effects of environmental stress is well documented. Cr functions as an antioxidant and its deficiency are said to disrupt carbohydrate and protein metabolism. Cr has been utilized for weight gain, to improve feed conversion ratio, increase relative organ weight, muscle development, decrease cholesterol, increase high density lipoprotein cholesterol, and improve nutrient digestion. Therefore, the present review discusses the beneficial aspects of Cr with its effect in different doses and antioxidant combinations to explore and promote its optimum utilization in poultry nutrition and production.
"They Were Really Looking for a Male Leader for the Building" Gender, Identity and Leadership Development in a Principal Preparation Program
Venue: Front. Psychol.

This study utilized a comparative case study analysis to investigate how gender influenced the experiences of participants in a leadership development program (principal preparation program) designed to lead public K 12 schools identified as requiring turnaround. We closely focused on two participants, a man and a woman, and compared the ways each participant made meaning of his/her experiences as developing leaders in the program. Although both participants conceptualized effective leadership in similar communally oriented ways, the way they came to construct their identities as leaders varied greatly. These differences were largely influenced by different and, what appeared to be, gendered feedback occurring during the program and when participants entered the job market.
Dual Server Public Key Encryption With Keyword Search for Secure Cloud Storage
Venue: IEEE Transactions on Information Forensics and Security

Searchable encryption is of increasing interest for protecting the data privacy in secure searchable cloud storage. In this paper, we investigate the security of a well known cryptographic primitive, namely, public key encryption with keyword search (PEKS) which is very useful in many applications of cloud storage. Unfortunately, it has been shown that the traditional PEKS framework suffers from an inherent insecurity called inside keyword guessing attack (KGA) launched by the malicious server. To address this security vulnerability, we propose a new PEKS framework named dual server PEKS (DS PEKS) As another main contribution, we define a new variant of the smooth projective hash functions (SPHFs) referred to as linear and homomorphic SPHF (LH SPHF) We then show a generic construction of secure DS PEKS from LH SPHF. To illustrate the feasibility of our new framework, we provide an efficient instantiation of the general framework from a Decision Diffie Hellman based LH SPHF and show that it can achieve the strong security against inside the KGA.
Locally Regularized Linear Regression in the Valuation of Real Estate

Regression methods are used for the valuation of real estate in the comparative approach. The basis for the valuation is a data set of similar properties, for which sales transactions were concluded within a short period of time. Large and standardized databases, which meet the requirements of the Polish Financial Supervision Authority, are created in Poland and used by the banks involved in mortgage lending, for example. We assume that in the case of large data sets of transactions, it is more advantageous to build local regression models than a global model. Additionally, we propose a local feature selection via regularization. The empirical research carried out on three data sets from real estate market confirmed the effectiveness of this approach. We paid special attention to the model quality assessment using cross validation for estimation of the residual standard error.
Quantifying polysemy: Corpus methodology for prototype theory

This study addresses the methodological problem of result falsification in Cognitive Semantics, specifically in the descriptive analysis of semasiological variation, or "polysemy" It argues that manually analysed corpus data can be used to describe models of semantic structure. The method proposed is quantified, permitting repeat analysis. The operationalisation of a semasiological structure employed in the study takes the principle of semantic features and applies them to a contextual analysis of usage events, associated with the lexeme under scrutiny. The feature analysis, repeated on a large collection of occurrences, results in a set of metadata that constitutes the usage profile of the lexeme. Multivariate statistics are then employed to identify patterns in those metadata. The case study examines 500 occurrences of the English lexeme annoy. Three basic senses are identified as well as a more complex array of semantic variations linked to morpho syntactic context of usage.
Improvement of Roller Bearing Diagnosis with Unlabeled Data Using Cut Edge Weight Confidence Based Tritraining

Roller bearings are one of the most commonly used components in rotational machines. The fault diagnosis of roller bearings thus plays an important role in ensuring the safe functioning of the mechanical systems. However, in most cases of bearing fault diagnosis, there are limited number of labeled data to achieve a proper fault diagnosis. Therefore, exploiting unlabeled data plus few labeled data, this paper proposed a roller bearing fault diagnosis method based on tritraining to improve roller bearing diagnosis performance. To overcome the noise brought by wrong labeling into the classifiers training process, the cut edge weight confidence is introduced into the diagnosis framework. Besides a small trick called suspect principle is adopted to avoid overfitting problem. The proposed method is validated in two independent roller bearing fault experiment vibrational signals that both include three types of faults: inner ring fault, outer ring fault, and rolling element fault. The results demonstrate the desirable diagnostic performance improvement by the proposed method in the extreme situation where there is only limited number of labeled data.
Shortest path and maximum flow problems in planar flow networks with additive gains and losses
Venue: ArXiv

In contrast to traditional flow networks, in additive flow networks, to every edge e is assigned a gain factor g(e) which represents the loss or gain of the flow while using edge e. Hence, if a flow f(e) enters the edge e and f(e) is less than the designated capacity of e, then f(e) g(e) 0 units of flow reach the end point of e, provided e is used, i.e. provided f(e) 0. In this report we study the maximum flow problem in additive flow networks, which we prove to be NP hard even when the underlying graphs of additive flow networks are planar. We also investigate the shortest path problem, when to every edge e is assigned a cost value for every unit flow entering edge e, which we show to be NP hard in the strong sense even when the additive flow networks are planar.