Effective distributed representations for academic expert search

Expert search aims to find and rank experts based on a user's query. In academia, retrieving experts is an efficient way to navigate through a large amount of academic knowledge. Here, we study how different distributed representations of academic papers (i.e. embeddings) impact academic expert retrieval. We use the Microsoft Academic Graph dataset and experiment with different configurations of a document-centric voting model for retrieval. In particular, we explore the impact of the use of contextualized embeddings on search performance. We also present results for paper embeddings that incorporate citation information through retrofitting. Additionally, experiments are conducted using different techniques for assigning author weights based on author order. We observe that using contextual embeddings produced by a transformer model trained for sentence similarity tasks produces the most effective paper representations for document-centric expert retrieval. However, retrofitting the paper embeddings and using elaborate author contribution weighting strategies did not improve retrieval performance.Comment: To be published in the Scholarly Document Processing 2020 Workshop @ EMNLP 2020 proceeding

Simulation of a data center cooling system in an emergency situation

The paper deals with keeping server rooms at reasonable air temperature in the case of an electrical power failure in a data center and with building performance simulations used to support emergency power planning. An existing data center was analyzed in detail with respect to the possibilities of emergency cooling. Based on the assumption that the thermal capacity of already chilled water can be used to prolong functionality of the cooling system when the roof chillers are out of operation, a backup power supply was designed for Computer Room Air-Conditioning and even for the cooling liquid circuit pumps (i.e. not for the roof chillers). Special models representing the data center indoor environment and cooling system, including a detailed model of the Computer Room Air Conditioning (CRAC) units, were developed in order to estimate the time period during which the internal air temperatures in the server room will not exceed the limit. The numerical model of the server room and the cooling system was built in the TRNSYS software and calibrated by measured data acquired from a real power outage situation. The results and conclusions obtained from the performed analyses and simulations helped to improve the emergency power plan of the data center. The study also forms the basis for the development of an emergency decision algorithm that will included in the novel supervisory control platform: GENi

Transcription Factor Efg1 Shows a Haploinsufficiency Phenotype in Modulating the Cell Wall Architecture and Immunogenicity of Candida albicans

The Candida albicans transcription factor Efg1 is known to be involved in many different cellular processes, including morphogenesis, general metabolism, and virulence. Here we show that besides its manifold roles, Efg1 also has a prominent effect on cell wall structure and composition, strongly affecting the structural glucan part. Deletion of only one allele of EFG1 already results in severe phenotypes for cell wall biogenesis, comparable to those with deletion of both alleles, indicative of a severe haploinsufficiency for EFG1. The observed defects in structural setup of the cell wall, together with previously reported alterations in expression of cell surface proteins, result in altered immunogenic properties of strains with compromised Efg1 function. This is shown by interaction studies with macrophages and primary dendritic cells. The structural changes in the cell wall carbohydrate meshwork presented here, together with the manifold changes in cell wall protein composition and metabolism reported in other studies, contribute to the altered immune response mounted by innate immune cells and to the altered virulence phenotypes observed for strains lacking EFG1

Microbial diversity and biogeochemical cycling in soda lakes

Soda lakes contain high concentrations of sodium carbonates resulting in a stable elevated pH, which provide a unique habitat to a rich diversity of haloalkaliphilic bacteria and archaea. Both cultivation-dependent and -independent methods have aided the identification of key processes and genes in the microbially mediated carbon, nitrogen, and sulfur biogeochemical cycles in soda lakes. In order to survive in this extreme environment, haloalkaliphiles have developed various bioenergetic and structural adaptations to maintain pH homeostasis and intracellular osmotic pressure. The cultivation of a handful of strains has led to the isolation of a number of extremozymes, which allow the cell to perform enzymatic reactions at these extreme conditions. These enzymes potentially contribute to biotechnological applications. In addition, microbial species active in the sulfur cycle can be used for sulfur remediation purposes. Future research should combine both innovative culture methods and state-of-the-art ‘meta-omic’ techniques to gain a comprehensive understanding of the microbes that flourish in these extreme environments and the processes they mediate. Coupling the biogeochemical C, N, and S cycles and identifying where each process takes place on a spatial and temporal scale could unravel the interspecies relationships and thereby reveal more about the ecosystem dynamics of these enigmatic extreme environments

Simulation of a data center cooling system in an emergency situation

The paper deals with keeping server rooms at reasonable air temperature in the case of an electrical power failure in a data center and with building performance simulations used to support emergency power planning. An existing data center was analyzed in detail with respect to the possibilities of emergency cooling. Based on the assumption that the thermal capacity of already chilled water can be used to prolong functionality of the cooling system when the roof chillers are out of operation, a backup power supply was designed for Computer Room Air-Conditioning and even for the cooling liquid circuit pumps (i.e. not for the roof chillers). Special models representing the data center indoor environment and cooling system, including a detailed model of the Computer Room Air Conditioning (CRAC) units, were developed in order to estimate the time period during which the internal air temperatures in the server room will not exceed the limit. The numerical model of the server room and the cooling system was built in the TRNSYS software and calibrated by measured data acquired from a real power outage situation. The results and conclusions obtained from the performed analyses and simulations helped to improve the emergency power plan of the data center. The study also forms the basis for the development of an emergency decision algorithm that will included in the novel supervisory control platform: GENi