nils-herrmann/clean_scirepeval huggingface dataset:
Ascitic fluid polymorphic nuclear cell count impacts on outcome of cirrhotic patients with ascites
Venue: United European gastroenterology journal
Year: 2019

Spontaneous bacterial peritonitis (SBP) is defined as an ascitic polymorphonuclear cell count (A PMN) 250 cells/ul.  We aimed to investigate the prognostic value of ascitic fluid cell counts in patients without SBP.  A total of 178 patients were included and stratified by ascitic cell counts at index paracentesis: A LEUK low <250/ul) A LEUK intermediate (250 500/ul) and A LEUK SBP >500/ul) for leukocytes; A PMN low <125/ul) A PMN intermediate (125 250/ul) and A PMN SBP >250/ul) for PMN cells.  One year mortality was comparable between group A LEUK SBP (53.9% and patients with subclinical cell counts (34.5% for A LEUK low, 43.5% for A LEUK intermediate, log rank p 0.547) However, we observed an increase in one year mortality already in group A PMN intermediate with 75% and A PMN SBP with 80.9% (vs 40.5% for A PMN low, log rank p 0.016) Importantly, increases of A PMN cell counts between two paracenteses were associated with increased mortality: per 100 cells/ul increase of absolute A PMN cell count: hazard ratio (HR) 1.03 (95% confidence interval (CI) 1.01 1.06) p 0.005; per 5% increase of relative PMN cell count: HR: 1.15 (95% CI: 1.06 1.26) p 0.001.  Patients with PMN cell counts of 125 250/ul are at high risk for mortality, which was very similar to SBP patients with PMN cell counts >250/ul. This highlights the need for preventive strategies. The prognostic value of changes in relative ascitic PMN cell counts should be evaluated in future studies.
Answer to the Letter to the Editor of V. B. Safer et al. concerning "Analysis of skeletal muscle mass in women over 40 with degenerative lumbar scoliosis" by Eguchi Y et al. (Eur Spine J; 2018: doi:10.1007/s00586 018 5845 0)
Venue: European Spine Journal
Year: 2019

We are truly grateful for the opportunity to respond to this Letter to the Editor concerning our recently published study entitled "Analysis of skeletal muscle mass in women over 40 with degenerative lumbar scoliosis"  First, we thank the authors for their interest in our work and for the opportunity to further explain our body composition analysis using the bioelectrical impedance analysis (BIA) and the classification of sarcopenia. BIA measures tissue impedance by circulating a weak alternating current through the hydrated tissues of the body [2] Measurement of appendicular skeletal muscle mass (ASMM) using dual energy X ray absorptiometry (DXA) is considered to be the gold standard for the diagnosis
Orbital Angular Momentum Mode Group Based Spatial Field Digital Modulation: Coding Scheme and Performance Analysis
Venue: 2020 IEEE International Conference on Communications Workshops (ICC Workshops)
Year: 2020

In this paper, we propose a concept of spatial field digital modulation (SFDM) and compare it with the conventional modulation to discuss the difference between them. Next, we explain the advantages of using orbital angular momentum (OAM) mode group to implement SFDM, and prove it by calculation. Then, SFDM system based on OAM mode group is proposed and theoretically analyzed. Finally, the influence of the system parameters to its anti noise performance is analyzed numerically.
An Innovative Social Model to Monitor Usage and Energy Performance of Public Real Estate based on ICT Applications
Year: 2014

After a review of some critical issues about usage and energy efficiency in public buildings, the paper describes Planergy(tm) a service model which supports public administrations to monitor their buildings. The service, which is distributed through a web platform www.Planergy.it represents an interesting social innovation since it directly involves workers and building users and since its results can be diffused as Open Data Sets. Its results can assist local administrators in developing a substantiated institutional communication and in adopting a sustainability reporting that takes into account both environmental and social consequences of their policies. Through the support of empirical data collected from its buildings, the administration can encourage specialists and firms in developing effective project proposals and it can motivate employees and the public towards energy efficiency good practices. In this way, an administration council can become a source of inspiration and good example to promote sustainable energy within its municipal area. Some preliminary operational results are outlined which are taken from the adoption of Planergy in a small municipality in the center Italy.
A pH responsive dissociable mesoporous silica based nanoplatform enabling efficient dual drug co delivery and rapid clearance for cancer therapy.
Venue: Biomaterials science
Year: 2020

The balance between tumor accumulation and renal clearance has severely limited the efficacy of mesoporous silica based drug nanocarriers in cancer therapy. Herein, a pH responsive dissociable mesoporous silica based nanoplatform with efficient dual drug co delivery, tumor accumulation and rapid clearance for cancer therapy is achieved by adjusting the wetting of the mesoporous silica surface. At pH 7.4, the synthesized spiropyran and fluorinated silane modified ultrasmall mesoporous silica nanoparticles (SP FS USMSN) self assemble to form larger nanoclusters (denoted as SP FS USMSN cluster) via hydrophobic interactions, which can effectively co deliver anticancer drugs, doxorubicin hydrochloride (Dox) and curcumin (Cur) based on the mesopores within SP FS USMSN and the voids among the stacked SP FS USMSN. At pH 4.5 5.5, the conformational conversion of spiropyran from a "closed" state to an "open" state causes the wetting of the SP FS USMSN surface, leading to the dissociation of the SP FS USMSN cluster for drug release and renal clearance. The in vitro and in vivo studies demonstrate that the Cur and Dox co loaded SP FS USMSN cluster (Cur Dox/SP FS USMSN cluster) possesses great combined cytotoxicity, and can accumulate into tumor tissue by its large size favored EPR effect and potently suppress tumor growth in HepG2 xenografted mice. This research demonstrates that the SP FS USMSN cluster may be a promising drug delivery system for cancer therapy and lays the foundation for practical mesoporous silica based nanomedicine designs in the future.
The Influence of Rewards on Employees Performance
Year: 2016

The study aims to examine the influence of reward types (extrinsic, intrinsic, social and rewards mix) on employees performance. Subjects for the study consisted of 308 workers which constituted 60% of the total target population of 513 people working for Unified Mining Companies located in the southern part of Jordan. Total of 308 self designed questionnaire were distributed to employees on their job location, 268 questionnaires were returned and only 250 were suitable for statistical analysis.  16 has been used for data analysis. Both descriptive and inferential statistics were used for data analysis. The statistical tools were aligned with the objective of the research. For this purpose, frequency Tables, percentages, means and standard deviations were computed and substantively interpreted. Inferential statistics like Pearson product moment correlation coefficient (r) was used to determine if there is a significant relationship exist between independent variables (rewards types: Extrinsic, intrinsic, social and rewards mix) and dependent variable (employees performance) Analysis and interpretation were made at 0.05 level of significance. The findings indicated that there is a statistical significant relationship between rewards types and employees performance. The study has concluded that, management should have deep sense of commitment towards the issue of rewarding employees, if performance levels to be enhanced. Finally, future research can be conducted to cover all types of rewards and to determine their affect on performance. Original Research Article Salah; BJEMT, 13(4) 1 25, 2016; Article no.BJEMT.25822 2
Alimentation et reseau social une etude sur le gout par necessite en contexte social
Year: 2014

L'influence de la societe sur les preferences alimentaires a fait l'objet de nombreuses etudes sans toutefois que ces dernieres tiennent compte des roles joues par les rapports sociaux. Bien que les celebres travaux sociologiques de Pierre Bourdieu mettent en evidence le lien entre le capital economique, culturel et social, et les choix alimentaires, tres peu d'etudes sur l'alimentation ont prete une attention empirique explicite au reseau social en tant que forme de capital social. Pour remedier a cette lacune, la presente recherche utilise les donnees provenant d'une etude de cohorte prospective sur la sante examinant les choix alimentaires de plusieurs milliers de personnes et ceux de leur reseau social immediat. Une comparaison entre les preferences alimentaires d'une personne et celles de son reseau social offre une nouvelle perspective sur la formation et le developpement des gouts et fournit de nouvelles preuves de l'influence des relations interpersonnelles sur les choix en matiere d'alimentation.
Pillar in Pillar: Multi Scale and Dynamic Feature Extraction for 3D Object Detection in Point Clouds
Venue: ArXiv
Year: 2019

Sparsity and varied density are two of the main obstacles for 3D detection networks with point clouds. In this paper, we present a multi scale voxelization method and a decomposable dynamic convolution to solve them. We consider the misalignment problem between voxel representation with different scales and present a center aligned voxelization strategy. Instead of separating points into individual groups, we use an overlapped partition mechanism to avoid the perception deficiency of edge points in each voxel. Based on this multi scale voxelization, we are able to build an effective fusion network by one iteration top down forward. To handle the variation of density in point cloud data, we propose a decomposable dynamic convolutional layer that considers the shared and dynamic components when applying convolutional filters at different positions of feature maps. By modeling bases in the kernel space, the number of parameters for generating dynamic filters is greatly reduced. With a self learning network, we can apply dynamic convolutions to input features and deal with the variation in the feature space. We conduct experiments with our PiPNet on KITTI dataset and achieve better results than other voxelization based methods on 3D detection task.
Engineering Parallel Algorithms for Community Detection in Massive Networks
Venue: IEEE Transactions on Parallel and Distributed Systems
Year: 2016

The amount of graph structured data has recently experienced an enormous growth in many applications. To transform such data into useful information, fast analytics algorithms and software tools are necessary. One common graph analytics kernel is disjoint community detection (or graph clustering) Despite extensive research on heuristic solvers for this task, only few parallel codes exist, although parallelism will be necessary to scale to the data volume of real world applications. We address the deficit in computing capability by a flexible and extensible community detection framework with shared memory parallelism. Within this framework we design and implement efficient parallel community detection heuristics: A parallel label propagation scheme; the first large scale parallelization of the well known Louvain method, as well as an extension of the method adding refinement; and an ensemble scheme combining the above. In extensive experiments driven by the algorithm engineering paradigm, we identify the most successful parameters and combinations of these algorithms. We also compare our implementations with state of the art competitors. The processing rate of our fastest algorithm often reaches 50 M edges/second. We recommend the parallel Louvain method and our variant with refinement as both qualitatively strong and fast. Our methods are suitable for massive data sets with billions of edges.
Securing Edge Devices in the Post Quantum Internet of Things Using Lattice Based Cryptography
Venue: IEEE Communications Magazine
Year: 2018

In order to increase the security of edge computing, all data transmitted to and from edge devices, as well as all data stored on edge devices, must be encrypted. Especially when the transmitted or stored data contains sensitive personal information, long term protection over periods of ten or more years may be required, which can only be achieved with post quantum cryptography. This article first gives a brief overview of post quantum public key cryptosystems based on hard mathematical problems related to hash functions, error correcting codes, multivariate quadratic systems, and lattices. Then the suitability of lattice based cryptosystems for resource constrained devices is discussed and efficient implementations for 8 and 32 bit microcontrollers are outlined.
Distributed robust data clustering in wireless sensor networks using diffusion moth flame optimization
Venue: Eng. Appl. Artif. Intell.
Year: 2020

Traditional K Means based distributed clustering used in wireless sensor networks has limitation of getting stuck into local minima, thus many times results in giving inaccurate cluster partitions. To alleviate this drawback, evolutionary based robust distributed clustering techniques are proposed in this paper. These techniques have the capability to determine the global optima thus results in effective cluster partitioning. A moth flame optimization based method is proposed here which minimizes the intra cluster distance to determine the optimal partition at every sensor node. A diffusion method of cooperation is employed by sharing the best moth position and corresponding fitness value (intra cluster distance) to the neighboring nodes. To introduce robustness, a weight based method for detection and removal of outliers is employed. In this method a weight based on volume and density is given to each data point for outlier detection, a larger weight is considered as an outlier. The simulation study is carried out on one synthetic and two real datasets. The performance of proposed approach is compared with diffusion particle swarm optimization (DPSO) diffusion whale optimization algorithm (DWOA) diffusion elephant herding optimization (DEHO) and distributed K Means (DK Means) in terms of Dunn's index, Silhouette index and time complexity. The minimum average Euclidean deviation of proposed diffusion moth flame optimization is 7.16% 3.25% 5.24% and 21.70% lower compared to DPSO, DWOA, DEHO and DK Means respectively for cook agronomy farm dataset.
Diagnostic tools for neurosyphilis: a systematic review
Venue: BMC Infectious Diseases
Year: 2021

Increasing incidences of syphilis highlight the preoccupation with the occurrence of neurosyphilis. This study aimed to understand the current diagnostic tools and their performance to detect neurosyphilis, including new technologies and the variety of existing methods.  We searched databases to select articles that reported neurosyphilis diagnostic methods and assessed their accuracy, presenting sensitivity and specificity values. Information was synthesized in tables. The risk of bias was examined using the Cochrane Handbook for Systematic Reviews of Diagnostic Test Accuracy recommendations.  Fourteen studies were included. The main finding was a remarkable diversity of tests, which had varied purposes, techniques, and evaluation methodologies. There was no uniform criterion or gold standard to define neurosyphilis. The current basis for its diagnosis is clinical suspicion and cerebrospinal fluid analysis. There are new promising tests such as PCR tests and chemokine measurement assays.  The diagnosis of neurosyphilis is still a challenge, despite the variety of existing and developing tests. We believe that the multiplicity of reference standards adopted as criteria for diagnosis reveals the imprecision of the current definitions of neurosyphilis. An important next step for the scientific community is to create a universally accepted diagnostic definition for this disease.
Recipe for success: lessons learnt from using xAPI within the connected learning analytics toolkit
Venue: LAK
Year: 2016

An ongoing challenge for Learning Analytics research has been the scalable derivation of user interaction data from multiple technologies. The complexities associated with this challenge are increasing as educators embrace an ever growing number of social and content related technologies. The Experience API (xAPI) alongside the development of user specific record stores has been touted as a means to address this challenge, but a number of subtle considerations must be made when using xAPI in Learning Analytics. This paper provides a general overview to the complexities and challenges of using xAPI in a general systemic analytics solution called the Connected Learning Analytics (CLA) toolkit. The importance of design is emphasised, as is the notion of common vocabularies and xAPI Recipes. Early decisions about vocabularies and structural relationships between statements can serve to either facilitate or handicap later analytics solutions. The CLA toolkit case study provides us with a way of examining both the strengths and the weaknesses of the current xAPI specification, and we conclude with a proposal for how xAPI might be improved by using JSON LD to formalise Recipes in a machine readable form.
E Mei 110 kVCai Tuo Bian Dian Zhan Bei Pin Bei Jian Guan Li Xi Tong Yan Jiu Research on the Management System of the 110 kV Intelligent Substation Spare Parts in Emei Cai Tuo Area
Year: 2017

Wei Mi Bu E Mei Cai Tuo Pian Qu 110 kVZhi Neng Bian Dian Zhan De Bei Pin Bei Jian Guan Li Fang Shi De Guan Li Que Xian ,Jie He Wu Lian Wang Si Wei Mo Shi Lai Gai Jin Bei Pin Bei Jian Guan Li Fang Shi ,Shi Xian Bei Pin Bei Jian Guan Li Jing Yi Hua ,Yi Jin Yi Bu Zeng Qiang Bian Dian Zhan Guan Li Zhi Neng Hua Cheng Du ,Ti Chu Bei Pin Bei Jian Zhi Neng Guan Li Xi Tong Ji Yu C#Kai Fa Ping Tai Yu Shu Ju Ku SQL Server 2005, Wu Lian Wang RFIDJi Zhu ,Jie He Wu Lian Wang Si Xiang She Ji Kai Fa Liao Bian Dian Zhan Bei Pin Bei Jian Shu Ju Guan Li Xi Tong ,Yi Dai Ti Chuan Tong Guan Li Fang Shi ,Ti Gao Bei Pin Bei Jian Guan Li Xiao Neng ,Cu Jin Liao Zhi Neng Bian Dian Zhan De Wan Shan Jian She ,You Xiao Bao Zhang Liao Guan Li Zhi Du ,Neng Gou Dui Bei Pin Bei Jian Neng You Xu Qie Zhun Que Di Jian Kong Yu Guan Li ,Ti Gao Liao Guan Li Gong Zuo Ke Kao Du ,Jie Yue Cheng Ben In order to remedy the managing defect of the management of spare parts at the 110 kv intelligent substation in Cai Tuo area, this paper put forward a intelligent management system of spare parts, which can improve the spare parts management and realize the lean management of spare parts by combining thinking of IOT. It also can further enhance the management level of intelligent substation. Spare parts data management system based on C# the database of SQL Server 2005 and RFID was designed and developed by combining with ideas of IOT. The spare parts data management system can monitor spare parts accurately instead of the traditional management of spare parts. It improves management efficiency and reliability of work, and it promotes the construction of smart substation. It also can security management system effectively and reduce the cost.
Anhedonia and emotional numbing in combat veterans with PTSD.
Venue: Behaviour research and therapy
Year: 2006

We explored relationships between anhedonia and posttraumatic stress disorder (PTSD) symptom clusters, including their role in predicting psychiatric comorbidity. Our measure of anhedonia was derived from an examination of the latent structure of the Beck Depression Inventory. We found evidence for a two factor solution, leading to anhedonia and undifferentiated, global depressive symptoms scales. In primary analyses, anhedonia had a unique positive relationship with PTSD's emotional numbing symptoms and minimal relationships with other PTSD symptoms. Upon examining the incremental validity of appetitive functioning (i.e. anhedonia, emotional numbing) over and above aversive functioning (i.e. re experiencing, avoidance, and hyper arousal PTSD symptoms) variables, greater emotional numbing increased the likelihood of being diagnosed with a major depressive disorder, and greater anhedonia increased the likelihood of being diagnosed with additional anxiety disorders and to a lesser extent, psychotic disorders. Results were consistent with research on the distinction of appetitive and aversive functioning, providing insight into the nature of PTSD.
Adsorption of Methylene Blue in Water onto Activated Carbon by Surfactant Modification
Year: 2020

In this paper, the enhanced adsorption of methylene blue (MB) dye ion on the activated carbon (AC) modified by three surfactants in aqueous solution was researched. Anionic surfactants sodium lauryl sulfate (SLS) and sodium dodecyl sulfonate (SDS) and cationic surfactant hexadecyl trimethyl ammonium bromide (CTAB) were used for the modification of AC. This work showed that the adsorption performance of cationic dye by activated carbon modified by anionic surfactants (SLS) was significantly improved, whereas the adsorption performance of cationic dye by activated carbon modified by cationic surfactant (CTAB) was reduced. In addition, the effects of initial MB concentration, AC dosage, pH, reaction time, temperature, real water samples, and additive salts on the adsorption were studied. When Na+ K+ Ca2+ NH4+ and Mg2+ were present in the MB dye solution, the effect of these cations was negligible on the adsorption <5% The presence of NO2 improved the adsorption performance significantly, whereas the removal rate of MB was reduced in the presence of competitive cation (Fe2+ It was found that the isotherm data had a good correlation with the Langmuir isotherm through analyzing the experimental data by various models. The dynamics of adsorption were better described by the pseudo second order model and the adsorption process was endothermic and spontaneous. The results showed that AC modified by anionic surfactant was effective for the adsorption of MB dye in both modeling water and real water.
Language, Identity and (In)Security in India Pakistan Relations: The Case of Kashmir
Year: 2017

This article revisits the Kashmir dispute by examining the interactions between language, religion and political dynamics to show how, in the post 1947 struggle, Kashmir's identity has increasingly been folded into the Indian and Pakistani language of a zero sum conflict and nationalistic self assertion. Paradoxically, Kashmir's position has weakened within a plural India even though Kashmir validates New Delhi's claim to religious and cultural heterogeneity. In Pakistan, Kashmir's diversity is dismissed because it disrupts Pakistan's unitary national identity centred on Islam and Urdu. By deliberately treating Kashmir as a homogenous Islamic entity, Pakistan seeks to attain legitimacy for its national imaginary as a pure Islamic state. Consequently, the capacity for Kashmir to actualise its own identity has diminished as it has been rendered hostage to the feuding of two behemoth 'imagined communities'
ESD Protection Design With Diode Triggered Quad SCR for Separated Power Domains
Venue: IEEE Transactions on Device and Materials Reliability
Year: 2019

To effectively protect the interface circuit between separated power domains from electrostatic discharge (ESD) damage, a new diode triggered quad silicon controlled rectifier (DTQSCR) is proposed and realized in a 0.18 \mu \text{m} 1.8 V/3.3 V CMOS process. Since the DTQSCR embeds four silicon controlled rectifier paths and a structure of back to back diodes, the silicon area can be efficiently reduced more than 30% as compared to the traditional ESD protection design under the same ESD specification. From the measurement results in silicon chip, an interface circuit (level shifter) with the proposed ESD protection design can successfully sustain a human body model of greater than 5.5 kV. The proposed ESD protection device is suitable to protect the interface circuits between different power domains.