Explainable methods for knowledge graph refinement and exploration via symbolic reasoning

Knowledge Graphs (KGs) have applications in many domains such as Finance, Manufacturing, and Healthcare. While recent efforts have created large KGs, their content is far from complete and sometimes includes invalid statements. Therefore, it is crucial to refine the constructed KGs to enhance their coverage and accuracy via KG completion and KG validation. It is also vital to provide human-comprehensible explanations for such refinements, so that humans have trust in the KG quality. Enabling KG exploration, by search and browsing, is also essential for users to understand the KG value and limitations towards down-stream applications. However, the large size of KGs makes KG exploration very challenging. While the type taxonomy of KGs is a useful asset along these lines, it remains insufficient for deep exploration. In this dissertation we tackle the aforementioned challenges of KG refinement and KG exploration by combining logical reasoning over the KG with other techniques such as KG embedding models and text mining. Through such combination, we introduce methods that provide human-understandable output. Concretely, we introduce methods to tackle KG incompleteness by learning exception-aware rules over the existing KG. Learned rules are then used in inferring missing links in the KG accurately. Furthermore, we propose a framework for constructing human-comprehensible explanations for candidate facts from both KG and text. Extracted explanations are used to insure the validity of KG facts. Finally, to facilitate KG exploration, we introduce a method that combines KG embeddings with rule mining to compute informative entity clusters with explanations.Wissensgraphen haben viele Anwendungen in verschiedenen Bereichen, beispielsweise im Finanz- und Gesundheitswesen. Wissensgraphen sind jedoch unvollständig und enthalten auch ungültige Daten. Hohe Abdeckung und Korrektheit erfordern neue Methoden zur Wissensgraph-Erweiterung und Wissensgraph-Validierung. Beide Aufgaben zusammen werden als Wissensgraph-Verfeinerung bezeichnet. Ein wichtiger Aspekt dabei ist die Erklärbarkeit und Verständlichkeit von Wissensgraphinhalten für Nutzer. In Anwendungen ist darüber hinaus die nutzerseitige Exploration von Wissensgraphen von besonderer Bedeutung. Suchen und Navigieren im Graph hilft dem Anwender, die Wissensinhalte und ihre Limitationen besser zu verstehen. Aufgrund der riesigen Menge an vorhandenen Entitäten und Fakten ist die Wissensgraphen-Exploration eine Herausforderung. Taxonomische Typsystem helfen dabei, sind jedoch für tiefergehende Exploration nicht ausreichend. Diese Dissertation adressiert die Herausforderungen der Wissensgraph-Verfeinerung und der Wissensgraph-Exploration durch algorithmische Inferenz über dem Wissensgraph. Sie erweitert logisches Schlussfolgern und kombiniert es mit anderen Methoden, insbesondere mit neuronalen Wissensgraph-Einbettungen und mit Text-Mining. Diese neuen Methoden liefern Ausgaben mit Erklärungen für Nutzer. Die Dissertation umfasst folgende Beiträge: Insbesondere leistet die Dissertation folgende Beiträge: • Zur Wissensgraph-Erweiterung präsentieren wir ExRuL, eine Methode zur Revision von Horn-Regeln durch Hinzufügen von Ausnahmebedingungen zum Rumpf der Regeln. Die erweiterten Regeln können neue Fakten inferieren und somit Lücken im Wissensgraphen schließen. Experimente mit großen Wissensgraphen zeigen, dass diese Methode Fehler in abgeleiteten Fakten erheblich reduziert und nutzerfreundliche Erklärungen liefert. • Mit RuLES stellen wir eine Methode zum Lernen von Regeln vor, die auf probabilistischen Repräsentationen für fehlende Fakten basiert. Das Verfahren erweitert iterativ die aus einem Wissensgraphen induzierten Regeln, indem es neuronale Wissensgraph-Einbettungen mit Informationen aus Textkorpora kombiniert. Bei der Regelgenerierung werden neue Metriken für die Regelqualität verwendet. Experimente zeigen, dass RuLES die Qualität der gelernten Regeln und ihrer Vorhersagen erheblich verbessert. • Zur Unterstützung der Wissensgraph-Validierung wird ExFaKT vorgestellt, ein Framework zur Konstruktion von Erklärungen für Faktkandidaten. Die Methode transformiert Kandidaten mit Hilfe von Regeln in eine Menge von Aussagen, die leichter zu finden und zu validieren oder widerlegen sind. Die Ausgabe von ExFaKT ist eine Menge semantischer Evidenzen für Faktkandidaten, die aus Textkorpora und dem Wissensgraph extrahiert werden. Experimente zeigen, dass die Transformationen die Ausbeute und Qualität der entdeckten Erklärungen deutlich verbessert. Die generierten unterstützen Erklärungen unterstütze sowohl die manuelle Wissensgraph- Validierung durch Kuratoren als auch die automatische Validierung. • Zur Unterstützung der Wissensgraph-Exploration wird ExCut vorgestellt, eine Methode zur Erzeugung von informativen Entitäts-Clustern mit Erklärungen unter Verwendung von Wissensgraph-Einbettungen und automatisch induzierten Regeln. Eine Cluster-Erklärung besteht aus einer Kombination von Relationen zwischen den Entitäten, die den Cluster identifizieren. ExCut verbessert gleichzeitig die Cluster- Qualität und die Cluster-Erklärbarkeit durch iteratives Verschränken des Lernens von Einbettungen und Regeln. Experimente zeigen, dass ExCut Cluster von hoher Qualität berechnet und dass die Cluster-Erklärungen für Nutzer informativ sind

Addressing the Scalability Bottleneck of Semantic Technologies at Bosch

At the heart of smart manufacturing is real-time semi-automatic decision-making. Such decisions are vital for optimizing production lines, e.g., reducing resource consumption, improving the quality of discrete manufacturing operations, and optimizing the actual products, e.g., optimizing the sampling rate for measuring product dimensions during production. Such decision-making relies on massive industrial data thus posing a real-time processing bottleneck

Tracy: Tracing facts over knowledge graphs and text

In order to accurately populate and curate Knowledge Graphs (KGs), it is important to distinguish s p o facts that can be traced back to sources from facts that cannot be verified. Manually validating each fact is time-consuming. Prior work on automating this task relied on numerical confidence scores which might not be easily interpreted. To overcome this limitation, we present Tracy, a novel tool that generates human-comprehensible explanations for candidate facts. Our tool relies on background knowledge in the form of rules to rewrite the fact in question into other easier-to-spot facts. These rewritings are then used to reason over the candidate fact creating semantic traces that can aid KG curators. The goal of our demonstration is to illustrate the main features of our system and to show how the semantic traces can be computed over both text and knowledge graphs with a simple and intuitive user interface

Ketamine as an adjunct to bupivacaine in infra-orbital nerve block analgesia after cleft lip repair

Abstract Objectives: We conducted this study to investigate the safety and analgesic efficacy of the addition of Ketamine to Bupivacaine in bilateral extra-oral infra-orbital nerve block in children undergoing cleft lip surgeries. Methods: Sixty patients were randomly allocated into two groups (n = 30), Group B received infra-orbital nerve block with 2 mL of 0.25% Bupivacaine and Group BK received 0.5 mg.kg-1 Ketamine for each side added to 1 mL of 0.5% Bupivacaine solution diluted up to 2 mL solution to 0.25% Bupivacaine concentration. Assessment parameters included; hemodynamics, recovery time, time to first oral intake, postoperative Faces Legs Activity Cry Consolability (FLACC) scores, Four-point Agitation scores, analgesic consumption and adverse effects. Results: Patients in Group BK showed lower postoperative FLACC scores during all recorded time points (p < 0.0001). Two patients in Group BK versus 12 in Group B requested for postoperative rescue analgesia (p < 0.001). There were no differences between groups in time, minutes (min), to first request for rescue analgesia. Patients in Group BK reported lower analgesic consumption (366.67 ± 45.67 vs. 240.0 ± 0.0 mg, p < 0.04). The time to first oral intake was significantly reduced in Group BK (87.67 ± 15.41 vs. 27.33 ± 8.68 min, p < 0.001). Lower postoperative Agitation scores were recorded in Group BK patients that reached a statistical significance at 45 min (0.86 ± 0.11 vs. 0.46 ± 0.16, p < 0.04) and in the first hour (h) postoperatively (1.40 ± 0.17 vs. 0.67 ± 0.14, p < 0.003). Higher parent satisfaction scores were recorded in Group BK (p < 0.04) without significant adverse effects. Conclusions: The addition of Ketamine to Bupivacaine has accentuated the analgesic efficacy of infra-orbital nerve block in children undergoing cleft lip repair surgeries

Ketamine as an adjunct to bupivacaine in infra-orbital nerve block analgesia after cleft lip repair

Objectives: We conducted this study to investigate the safety and analgesic efficacy of the addition of Ketamine to Bupivacaine in bilateral extra-oral infra-orbital nerve block in children undergoing cleft lip surgeries. Methods: Sixty patients were randomly allocated into two groups (n = 30), Group B received infra-orbital nerve block with 2 mL of 0.25% Bupivacaine and Group BK received 0.5 mg.kg−1 Ketamine for each side added to 1 mL of 0.5% Bupivacaine solution diluted up to 2 mL solution to 0.25% Bupivacaine concentration. Assessment parameters included; hemodynamics, recovery time, time to first oral intake, postoperative Faces Legs Activity Cry Consolability (FLACC) scores, Four-point Agitation scores, analgesic consumption and adverse effects. Results: Patients in Group BK showed lower postoperative FLACC scores during all recorded time points (p < 0.0001). Two patients in Group BK versus 12 in Group B requested for postoperative rescue analgesia (p < 0.001). There were no differences between groups in time, minutes (min), to first request for rescue analgesia. Patients in Group BK reported lower analgesic consumption (366.67 ± 45.67 vs. 240.0 ± 0.0 mg, p < 0.04). The time to first oral intake was significantly reduced in Group BK (87.67 ± 15.41 vs. 27.33 ± 8.68 min, p < 0.001). Lower postoperative Agitation scores were recorded in Group BK patients that reached a statistical significance at 45 min (0.86 ± 0.11 vs. 0.46 ± 0.16, p < 0.04) and in the first hour (h) postoperatively (1.40 ± 0.17 vs. 0.67 ± 0.14, p < 0.003). Higher parent satisfaction scores were recorded in Group BK (p < 0.04) without significant adverse effects. Conclusions: The addition of Ketamine to Bupivacaine has accentuated the analgesic efficacy of infra-orbital nerve block in children undergoing cleft lip repair surgeries. Resumo: Objetivos: Realizamos este estudo para avaliar a segurança e eficácia da analgesia com a adição de cetamina à bupivacaína em bloqueio do nervo infraorbitário, bilateral e extraoral, em crianças submetidas à cirurgia de lábio leporino. Métodos: Foram randomicamente alocados 60 pacientes em dois grupos (n = 30): o Grupo B recebeu bloqueio do nervo infraorbitário com bupivacaína a 0,25% (2 mL) e o Grupo BC recebeu bloqueio com cetamina (0,5 mg.kg−1) em cada lado, mais a adição de 1 mL de solução de bupivacaína a 0,5% diluída até 2 mL da concentração a 0,25%. Os parâmetros de avaliação incluíram: hemodinâmica, tempo de recuperação, tempo até a primeira ingestão oral, escores da escala FLACC (que avalia a expressão facial [Face], os movimentos das pernas [Legs], a atividade [Activity], o choro [Cry] e a consolabilidade [Consolability]), escores de agitação em escala de quatro pontos, consumo de analgésicos e efeitos adversos no pós-operatório. Resultados: Os pacientes do Grupo BC apresentaram escores FLACC mais baixos em todos os momentos mensurados no pós-operatório (p < 0,0001). Dois pacientes do Grupo BC versus 12 do Grupo B solicitaram analgesia de resgate no pós-operatório (p < 0,001). Não houve diferenças entre os grupos em relação ao tempo até a primeira solicitação de analgesia de resgate. Os pacientes do Grupo BC relataram consumo menor de analgésicos (366,67 ± 45,67 vs. 240,0 ± 0,0 mg, p < 0,04). O tempo em minutos (min) até a primeira ingestão oral foi significativamente reduzido no Grupo BC (87,67 ± 15,41 vs. 27,33 ± 8,68 min, p < 0,001). Escores mais baixos de agitação no pós-operatório foram registrados para os pacientes do Grupo BC, com significância estatística no tempo de 45 min (0,86 ± 0,11 vs. 0,46 ± 0,16; p < 0,04) e na primeira hora de pós-operatório (1,40 ± 0,17 vs. 0,67 ± 0,14; p < 0,003). Índices mais altos de satisfação dos pais foram registrados no Grupo BC (p < 0,04), sem efeitos adversos significativos. Conclusões: A adição de cetamina à bupivacaína acentuou a eficácia analgésica do bloqueio do nervo infraorbitário em crianças submetidas à cirurgia de correção de lábio leporino. Keywords: Postoperative pain, Cleft lip, Local analgesia, Infra-orbital nerve, Bupivacaine, Ketamine, Palavras-chave: Dor pós-operatória, Lábio leporino, Analgesia local, Nervo infraorbitário, Bupivacaína, Cetamin

sj-docx-1-ppj-10.1177_17504589231221642 – Supplemental material for The impact of ketamine on delayed neurocognitive recovery in elderly patients undergoing spinal anaesthesia for orthopaedic procedures, a pilot study

Supplemental material, sj-docx-1-ppj-10.1177_17504589231221642 for The impact of ketamine on delayed neurocognitive recovery in elderly patients undergoing spinal anaesthesia for orthopaedic procedures, a pilot study by Mostafa Samy Abbas, Mohamed Gamal Abo-Zeid, Fatma Gad-Elrab Askar and Omnia Ahmed Askar in Journal of Perioperative Practice</p

Rapid detection of circulating fibrocytes by flowcytometry in idiopathic pulmonary fibrosis

Background: Current protocols for detection of circulating fibrocytes (CFs) in peripheral blood described in various pulmonary and nonpulmonary disorders involve complex and time consuming, non standardized techniques. Objective: Testing a method to rapidly detect and quantify CFs using whole blood lysis flow cytometry-based assay in patients with idiopathic pulmonary fibrosis (IPF) and healthy controls. Methods: One milliliter of venous blood sample in ethylenediaminetetraacetic acid (EDTA) from 33 IPF patients and 35 healthy control subjects was collected. Using whole blood lysis method peripheral blood leukocytes were labeled with monoclonal antibodies for cell surface (CD34 and CD45) and intracellular markers (collagen-1) for flow cytometric analysis. CFs were defined as CD45 + cells coexpressing collagen-I and CD34 molecules. Results: In 29 (87.8%) IPF patients and 10 (28.5%) control subjects, a well-defined highly granular CD45 + cell population was detected in dot plots generated by side scatter properties of CD45 + cells. These CD45 + cells were identified as CFs on the basis of coexpression of collagen-I and CD34; none of the other cell types in the peripheral blood were labeled with these monoclonal antibodies. In IPF patients the percentage of CFs was significantly higher compared to healthy controls (median (range): 1.37% (0.52-5.65) and 1.04% (0.1-1.84), respectively; P = 0.03). Conclusions: Whole blood lysis method combined with fluorescence-activated cell sorting (FACS) allows detecting a well-defined homogeneous population of CFs. This method is simple, reproducible, and provides an accurate and rapid estimation of CFs