Special Nature Research Articles

The legal organization of the crime of child begging in light of Iraqi legislation

The crime of begging is spreading rapidly in most societies, especially in developing countries, where this crime has become a negative and dangerous impact on the social, economic and cultural levels. The reasons associated with this crime are many and varied, some of which may be due to the individual himself, in addition to the factors that affect society. Accordingly, our study deals with the topic of "the legal organization of the crime of child begging in the light of Iraqi and comparative legislation", especially since the category of children is characterized by its special and vulnerable nature, in addition to the fact that the impact of this crime is increasing in seriousness in light of modern technological and technological developments. In light of these challenges and in view of the importance of the child who enjoys protection and care in the majority of societies, many positive legislations have resorted to working to draw a legal structure that suits the special nature of the child "juvenile", by deciding reform measures that suit each juvenile individually and according to his circumstances and personality, which was followed by Iraqi legislation. The study raises the problem of combating begging crimes committed by children, because it deals with many legal, social and psychological aspects, in addition to preventive and precautionary measures, as well as demonstrating the ability of Iraqi legislation to confront. Our study was divided into two topics; we dealt in the first with the crime of child begging, and in the second we dealt with the elements of the crime of child begging and its penalties.

Numerical analysis of fluid-thermal-structure coupling characteristics of CO2 booster pump valve

CO2 booster pump valves are key components in the CO2 oil drive industry, and their reliability is critical to the safe operation of pumping booster systems. Due to the special nature of CO2, heat transfer occurs during valve movement, which can cause damage to the valve body and poppet, and thus in-depth studies on CO2 properties are needed to better predict the locations where the valve is vulnerable to damage. However, relatively few studies have been conducted to analyze the fluid-thermal-solid coupling failure of CO2 booster pump valves. This paper establishes a multi-physics coupled thermodynamic model of CO2 booster pump valves, analyzes the transient simulation of valves at different valve openings, pressures and temperatures, and investigates the thermal properties of four different poppet materials. The results show that: with the increase of valve opening, the maximum deformation of the valve decreases sharply, and then tends to stabilize; in the process of pressure increasing from 4.77 MPa to 10.52 MPa, the turbulent kinetic energy inside the valve increases by about 78 %; it is also found that the thermal deformation of different poppet materials is directly proportional to the coefficients of thermal expansion of the materials, among which the deformation of aluminum alloy poppet is the largest. In addition, the results of thermal deformation and thermal stress distribution indicate that the failure region of the valve is usually concentrated in the poppet and its corresponding body wall. These results provide theoretical references for optimizing the structural design of CO2 booster pump valves and help reduce the risk of failure of CO2 booster pump valves.

Understanding Patient Flow from the Perspectives of Patient Movement Experts

Background: Poor patient flow or patient movement through a healthcare organisation can lead to adverse outcomes for patients and organisational inefficiency. Many hospitals have addressed suboptimal patient flow by increasing resources, such as bed stock and staffing; however, this is an unsustainable approach. In determining the nature of poor patient flow issues, it is important to collect data from healthcare professionals who manage patient flow daily. Doing so provides insights into the current state of patient flow management in its entirety, whilst also helping with the development of sustainable solutions. Methods: Thirteen semi-structured interviews were conducted with healthcare professionals who were directly involved with patient flow at a referring hospital in Tasmania, Australia. Results: Using a thematic analysis method, four major themes were developed. The first major theme was: ‘managing patient flow’ which centered around known and unknown demands on bed availability. The second theme, ‘communication for decisions’, highlighted the essential role of communication in maintaining patient flow. The third theme, ‘tools as enablers and barriers, relates to the number of software programs which can both help and hinder patient flow. The final theme of ‘increasing complexity’ is related to an apparent trend towards greater numbers of patients requiring care of an increasingly specialised nature. Conclusions: The findings of this study provide great insights into patient flow issues, with potential solutions identified to address them.

Risk Management of Supply Chain in Prefabricated Buildings: A Case Study of Leishenshan Hospital

Based on the research of other scholars, this article divides the prefabricated building supply chain into six stages: design and development, production procurement, warehousing and transportation, lifting construction, and facility recycling. Taking the well-known prefabricated building of Leishenshan Hospital as an example, this study analyzes the possible risks of these six stages in the prefabricated building supply chain, such as insufficient design capabilities, production efficiency, the low standardization level of molds, transportation policy constraints, insufficient protection of components during the warehousing and transportation stage, insufficient organizational capacity, inadequate supervision, and problems such as missing recycling processes. Due to the special nature of Leishenshan Hospital, which has received great attention, some risks that have been avoided due to special reasons have been proposed, and the power of management personnel has been strengthened for these risks, digitization and standardization of molds, and strengthen on-site management level. From this study, construction, component production, and design enterprises can learn from measures such as increasing awareness of component recycling.

Modelling and experimental study on pipeline defect characterisations using a pulsed eddy current measurement

ABSTRACT Pipelines are widely used as the main transportation method in petrochemical and metallurgical industries. However, the special nature of the materials transported in pipelines means they are often subjected to high temperature, high pressure and corrosive conditions. This can lead to defects, such as thinning and cracking, resulting in pipeline failure and causing serious economic losses. Therefore, regular non-destructive testing of pipelines is particularly important. This paper uses the non-destructive testing method with pulsed eddy current technology to characterise pipeline thinning and defects. A preliminary study is conducted on the pulsed eddy current detection signal patterns for pipeline crack defects with varying orientations and quantities. A more portable pulsed eddy current detection device with an extended wall thickness detection range is developed. It can achieve measurements with a maximum thickness of 30 mm for detections of pipelines with rectangular defects and thickness-stepped reduced. The experimental results are consistent with modelling results, and the accuracy for pipelines with insulation layer is also investigated. On-site measurements using the PEC system are conducted on equipment sections with pipe thickness within 20 mm in a petrochemical plant. It is confirmed that the developed PEC inspection device can accurately characterises the thickness of pipelines with 0–50 mm cladding.

From pre-training to fine-tuning: An in-depth analysis of Large Language Models in the biomedical domain

In this study, we delve into the adaptation and effectiveness of Transformer-based, pre-trained Large Language Models (LLMs) within the biomedical domain, a field that poses unique challenges due to its complexity and the specialized nature of its data. Building on the foundation laid by the transformative architecture of Transformers, we investigate the nuanced dynamics of LLMs through a multifaceted lens, focusing on two domain-specific tasks, i.e., Natural Language Inference (NLI) and Named Entity Recognition (NER). Our objective is to bridge the knowledge gap regarding how these models’ downstream performances correlate with their capacity to encapsulate task-relevant information. To achieve this goal, we probed and analyzed the inner encoding and attention mechanisms in LLMs, both encoder- and decoder-based, tailored for either general or biomedical-specific applications. This examination occurs before and after the models are fine-tuned across various data volumes. Our findings reveal that the models’ downstream effectiveness is intricately linked to specific patterns within their internal mechanisms, shedding light on the nuanced ways in which LLMs process and apply knowledge in the biomedical context. The source code for this paper is available at https://github.com/agnesebonfigli99/LLMs-in-the-Biomedical-Domain.

ChatGPT Solving Complex Kidney Transplant Cases: A Comparative Study With Human Respondents.

ChatGPT has shown the ability to answer clinical questions in general medicine but may be constrained by the specialized nature of kidney transplantation. Thus, it is important to explore how ChatGPT can be used in kidney transplantation and how its knowledge compares to human respondents. We prompted ChatGPT versions 3.5, 4, and 4 Visual (4V) with 12 multiple-choice questions related to six kidney transplant cases from 2013 to 2015 American Society of Nephrology (ASN) fellowship program quizzes. We compared the performance of ChatGPT with US nephrology fellowship program directors, nephrology fellows, and the audience of the ASN's annual Kidney Week meeting. Overall, ChatGPT 4V correctly answered 10 out of 12 questions, showing a performance level comparable to nephrology fellows (group majority correctly answered 9 of 12 questions) and training program directors (11 of 12). This surpassed ChatGPT 4 (7 of 12 correct) and 3.5 (5 of 12). All three ChatGPT versions failed to correctly answer questions where the consensus among human respondents was low. Each iterative version of ChatGPT performed better than the prior version, with version 4V achieving performance on par with nephrology fellows and training program directors. While it shows promise in understanding and answering kidney transplantation questions, ChatGPT should be seen as a complementary tool to human expertise rather than a replacement.

Ukraine on Fire Cinema Novel by Oleksandr Dovzhenko: Saving Gesture of the Artist

The years of German-Soviet war (1941–1945) have become a period of special trials for the outstanding film director Oleksandr Dovzhenko. All hopes for the revival of the Ukrainian nation and its culture have turned out to be an illusion. The victory of the Soviet Union in the war has led to the collapse of the remnants of political and cultural autonomy in Ukraine, complete control of the imperial center over the processes of social and cultural life. Dovzhenko writes the film story Ukraine on Fire, which demonstrates the considerable resources of resistance of Ukrainians to totalitarian systems – both Soviet and German. In addition, Dovzhenko as an author reveals the intention of a national prophet who believes in his magical ability to save his people. The author has special sympathy for Ukrainian girls and women. They are killed, raped, humiliated. However, they remain special bearers of the nation mentality, its cultural and artistic memory. Its beauty! Therefore, the images of women are permeated with folklore and literary motifs, those voice out and materialize the world of Ukrainians who oppose the war. The story has drawn a lot of criticism from the dictator Stalin, criticism made public during a special meeting in the Kremlin. The accusations have been reduced to alleged manifestations of nationalism, revision of the very foundations of the Bolshevik empire. The work has been banned from publication and production in the cinema. Today, in the context of the new stage of war of the Russian Empire against Ukraine, the work in which the artist at the time of the disaster, is on the edge of the abyss and the non-existence of the people, comes to its defense, acquires special relevance and worldview expressiveness. Ukraine on Fire is distinguished by the special lyrical nature of the text, it is permeated with folk singing, folklore images and even rhythm. An amazing consonance with the folk melos, a powerful lyric-epic coverage of folk life. The completion of work on the film story has coincided with the beginning of the stay of Dovzhenko’s mother, Odarka Yermolaivna, in Moscow, in Dovzhenko’s apartment (after the end of the German occupation of Kyiv). The artist has recorded a number of folk songs from her, those have a significant impact on the work on the following scenarios – Chronicle of Flaming Years, Enchanted Desna, Poem of the Sea.

Nurses' Adherence to Infection Control Practices in Emergency Departments

Background: Follow-Up on Infection Prevention Measures It is an assortment of techniques intended to keep things free of microbes, Patient protection from diseases necessitates several actions. Preventing and controlling infections is one of the most crucial tasks for nurses. Using hand hygiene with personal protection equipment is a crucial step that can help prevent infections or their repercussions. The safety of patients and maintaining sterility and cleanliness in hospitals are the responsibilities of all nurses working there. Objectives: to evaluate the adherence of emergency department nurses to infection control protocols and recommendations. Methodology: This cross-sectional study selected a nonprobability (purposive) sample of 120 nurses working in emergency departments across three hospitals: Baghdad Teaching Hospital (50%), Al-Kindy Teaching Hospital (35.8%), and Sheik Zaydi Hospital 14.2%. The study was conducted from September 20, 2023, to 30 June 2024. collection tool, which consists of two parts: The first part is the demographic characteristics of the nursing staff (age, gender, level of education, years of experience in the emergency department, and participation in training courses related to infection control measures). Second part: Checklists were utilized for observation. The study instrument's reliability was assessed using the Statistical Package for Social Science Program (IBM SPSS) by applying Cronbach's Alpha. Results: The study finding shows that, based on the data, 66.7% of the respondents reported a fair level of practices about infection control measures. Sociodemographic factors such as qualifications notably impact nurses' practices regarding adherence to infection control practices. CONCLUSIONS: The researcher concluded that the nurses' practices were not at the level required (fair) to fit with the critical and special nature of the emergency department. Recommendations: Standard precautions are the basic level of the infection control process. The participants may possess satisfactory knowledge and compliance levels. However, more training programs and more focus on the standard precautions by educational institutes are needed for nurses to improve their knowledge and compliance with infection-control standard precautions.

Banditry or Peasant Insurgency? Contextualizing and Analysing the Chuar Rebellion of Midnapore Under East India Company (1770s–1800)

Midnapore was one among the first three districts ceded to the East India Company in 1760 by Mir Qasim, the other two being Burdwan and Chittagong. Following this, the acquisition of the diwani of Bengal, Bihar and Orissa in 1765 launched the East India Company into a complex administrative role related to revenue in an alien territory with complex, multi-tiered, customary land rights that were beyond their knowledge. Their attempts at revenue collection and the accompanying imposition of a legal, rational state on a customary framework led to tragedies like the Bengal famine of 1770. It served as the impetus for the initial uprisings against colonial rule, which mainstream accounts on resistances in the early colonial period tend to omit. The study here aims to shed light on the nature of rule transition and complexities regarding land ownership that the Company encountered, the special nature of Midnapore frontier, and phases of the chuar rebellion pre- and post Permanent Settlement. Special attention has been placed on conceptual clarification of chuars, paiks, their status overlaps and subalternity and on analysing the nature of the rebellion in the light of Eric Hobsbawm’s concept of banditry and Ranajit Guha’s analysis on features of peasant insurgency in colonial India.

GCP: A multi-strategy improved wireless sensor network model for environmental monitoring

Nowadays, smart environmental monitoring devices are widely used in various fields, and one of the most representative tools is the wireless sensor network (WSN). WSNs are easy to deploy and provide real-time information feedback, which is very suitable for environmental monitoring. As we all know, the environmental monitoring network because of the special nature of its work requirements, the need for uninterrupted and real-time transmission of monitoring data, which leads to energy consumption is extremely large, and this cannot meet the needs of its long-term work. Existing traditional routing has problems such as unscientific cluster head election and high redundancy in data transmission, which usually lead to a large amount of energy consumption, which is not conducive to the long-term stable operation of sensor networks. In this paper, we improve the traditional routing protocol and design a cluster head election method based on the genetic algorithm, which proposes a new fitness function in terms of energy, distance, and the number of nodes in the cluster, and performs the selection of cluster head nodes based on this method. In addition, we propose a new grey prediction model, which can realize the real-time update of data queues, and optimize the data transmission process of traditional WSNs based on this prediction model to reduce the amount of intra-cluster data transmission. Combining these improvements, a grey cluster prediction (GCP) model is proposed, and the performance of the model is tested based on real mine and soil data sets. The simulation results show that the model significantly reduces energy loss and extends the network life cycle while ensuring the integrity of data transmission. It can also meet the requirements of long-term stable operation of environmental monitoring equipment.

Chinese EMR Named Entity Recognition Using Fused Label Relations Based on Machine Reading Comprehension Framework.

Chinese electronic medical record (EMR) presents significant challenges for named entity recognition (NER) due to their specialized nature, unique language features, and diverse expressions. Traditionally, NER is treated as a sequence labeling task, where each token is assigned a label. Recent research has reframed NER within the machine reading comprehension (MRC) framework, extracting entities in a question-answer format, achieving state-of-the-art performance. However, these MRC-based methods have a significant limitation: they extract entities of various types independently, ignoring their interrelations. To address this, we introduce the Fusion Label Relations with MRC (FLR-MRC) model, which enhances the MRC model by implicitly capturing dependencies among entity types. FLR-MRC models interrelations between labels using graph attention networks, integrating these with textual data to identify entities. On the benchmark CMeEE and CCKS2017-CNER datasets, FLR-MRC achieves F1-scores of 0.6652 and 0.9101, respectively, outperforming existing clinical NER methods.

Dual-branch Transformer for semi-supervised medical image segmentation.

In recent years, the use of deep learning for medical image segmentation has become a popular trend, but its development also faces some challenges. Firstly, due to the specialized nature of medical data, precise annotation is time-consuming and labor-intensive. Training neural networks effectively with limited labeled data is a significant challenge in medical image analysis. Secondly, convolutional neural networks commonly used for medical image segmentation research often focus on local features in images. However, the recognition of complex anatomical structures or irregular lesions often requires the assistance of both local and global information, which has led to a bottleneck in its development. Addressing these two issues, in this paper, we propose a novel network architecture. We integrate a shift window mechanism to learn more comprehensive semantic information and employ a semi-supervised learning strategy by incorporating a flexible amount of unlabeled data. Specifically, a typical U-shaped encoder-decoder structure is applied to obtain rich feature maps. Each encoder is designed as a dual-branch structure, containing Swin modules equipped with windows of different size to capture features of multiple scales. To effectively utilize unlabeled data, a level set function is introduced to establish consistency between the function regression and pixel classification. We conducted experiments on the COVID-19 CT dataset and DRIVE dataset and compared our approach with various semi-supervised and fully supervised learning models. On the COVID-19 CT dataset, we achieved a segmentation accuracy of up to 74.56%. Our segmentation accuracy on the DRIVE dataset was 79.79%. The results demonstrate the outstanding performance of our method on several commonly used evaluation metrics. The high segmentation accuracy of our model demonstrates that utilizing Swin modules with different window sizes can enhance the feature extraction capability of the model, and the level set function can enable semi-supervised models to more effectively utilize unlabeled data. This provides meaningful insights for the application of deep learning in medical image segmentation. Our code will be released once the manuscript is accepted for publication.

A Novel Rational Medicine Use System Based on Domain Knowledge Graph

Medication errors, which could often be detected in advance, are a significant cause of patient deaths each year, highlighting the critical importance of medication safety. The rapid advancement of data analysis technologies has made intelligent medication assistance applications possible, and these applications rely heavily on medical knowledge graphs. However, current knowledge graph construction techniques are predominantly focused on general domains, leaving a gap in specialized fields, particularly in the medical domain for medication assistance. The specialized nature of medical knowledge and the distinct distribution of vocabulary between general and biomedical texts pose challenges. Applying general natural language processing techniques directly to the medical domain often results in lower accuracy due to the inadequate utilization of contextual semantics and entity information. To address these issues and enhance knowledge graph production, this paper proposes an optimized model for named entity recognition and relationship extraction in the Chinese medical domain. Key innovations include utilizing Medical Bidirectional Encoder Representations from Transformers (MCBERT) for character-level embeddings pre-trained on Chinese biomedical corpora, employing Bi-directional Gated Recurrent Unit (BiGRU) networks for extracting enriched contextual features, integrating a Conditional Random Field (CRF) layer for optimal label sequence output, using the Piecewise Convolutional Neural Network (PCNN) to capture comprehensive semantic information and fusing it with entity features for better classification accuracy, and implementing a microservices architecture for the medication assistance review system. These enhancements significantly improve the accuracy of entity relationship classification in Chinese medical texts. The model achieved good performance in recognizing most entity types, with an accuracy of 88.3%, a recall rate of 85.8%, and an F1 score of 87.0%. In the relationship extraction stage, the accuracy reached 85.7%, the recall rate 82.5%, and the F1 score 84.0%.

Государственный суверенитет в координатах судебной власти: суверенна ли судебная власть?

The article presents the author's concept of judicial sovereignty, which is based on an analysis of the constitutional characteristics of the sovereign principles of the judiciary, which include: the increased, special nature of the legitimacy of the judiciary; the unity of the judicial system of the Russian Federation, ensuring the unity of judicial sovereignty; the independence of the court; the jurisdictional universalism of the court, ensured by the exercise of judicial power in various constitutional forms of legal proceedings, by combining universalization with differentiation; judicial and jurisdictional discretion, including the possibilities of judicial law-making and the formation of judicial law. In this regard, the concept of judicial sovereignty is being implemented both in law enforcement, judicial and jurisdictional activities, and in judicial rulemaking. At the same time, the role of the judiciary in the development of the modern doctrine of state sovereignty is analyzed, bearing in mind, first of all, the decisions of the Constitutional Court of the Russian Federation as the conceptual basis of national judicial jurisprudence, which is of particular relevance in modern conditions of the global crisis of international relations and the need to strengthen the sovereignty of Russia in all forms of its manifestation.

Preparation and properties of ultra-thin-walled energy storage paraffin microcapsules for naval applications

Due to the special nature of weather conditions at sea, the tricky status quo of heat loss in readiness or operational clothing, there is an urgent need for special insulated clothing materials to withstand harsh environments, maintain body temperature, and increase comfort for naval personnel who have been at sea for a long period of time in preparation for battle or combat. Paraffin is a special kind of phase change energy storage material, And the preparation of paraffin microcapsules is an effective way to solve the above problems, in which the ultra-thin-walled energy storage paraffin capsules have the advantages of large volume, accommodating more paraffin phase change materials, good energy storage effect and low cost. In this study, three kinds of paraffin microcapsules with core-shell structure were prepared by encapsulating a membrane with stable performance on the surface of paraffin particles using microencapsulation and layer-by-layer self-assembly techniques. We characterized their thermal storage capacity, composition and morphology by thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), Fourier infrared spectroscopy, and optical microscopy, and compared their performances. The results show that the paraffin microcapsules prepared by layer-by-layer (LBL) self-assembly technique in this study have good thermal storage performance and stability, and their thickness increases with the increase of the number of layers, and the materials used in the experiment wrapped the liquid paraffin layer by layer, which is expected to be practically applied in the field of naval energy storage materials.

Opportunities And Threats Of Historical Evidence And Data Via Corpus-Based Software: A Case Study On Gerard Malynes

The aim of this paper is to exploit the informative nature of datasets that can be created from corpus-based software to explore specific phenomena in early modern specialized discourse, and to corroborate the adoption of the same software for historical analysis. Particular relevance will be devoted to the special nature of historical evidence, which has caused critical issues in the reliability of the data collected for the purpose of historical investigation of English. Spelling variation, in this sense, is one of the most crucial problems of Early Modern English, and this has often affected the reliability of data to be collected via software, especially when statistical findings are involved. The normalisation of historical texts has contributed enormously to make texts better readable for historical corpus analysis; and, consequently, to improve the accuracy and manipulation of data. Moreover, several tools used in corpus linguistics have benefited from the normalisation of spelling variants in the same terms, e.g. part-of-speech taggers for historical variety. This case study will attempt to explore the data retrievable from corpus-based software like VARD, #LancsBox and CQPweb, and to use them to corroborate a preliminary analysis of early modern economics discourse in two treatises written by Gerard Malynes in 1601 and 1623.

المحيط الجامعي بالمغرب: البنية والرضا

The current study aims to know the structure and level of satisfaction of Moroccan students with their university surroundings based on the 70-phrase level measure of satisfaction with the university's surroundings, divided into 7 items, Of interest to the various aspects of the university environment, the research sample included 359 students; This made the measurement achieved to achieve a good internal consistency rate of 0.95 alpha Cronbach approach", demonstrating the appropriateness of adopting this measure to study the varying satisfaction with the university environment of this sample. In the same vein, the working analysis of the scale items assures us that the university surroundings are a compilation of two components, the first being a physical element linked to infrastructure, and the other, not a material element encompassing the relational and organizational aspect of the results that show that students are not satisfied with: Facilities and facilities, university services, pedagogical equipment, study process, curricula, and examinations. In return, we find them satisfied with the relationship that brings them together with other colleagues and educational and administrative staff. We have also found that satisfaction clauses are influenced by different sociodemographic variables studied, for example: the level of satisfaction in examinations varies by sex, as does the nature of the student's specialization, as the level of satisfaction with pedagogical methods and curricula changes. It is also clear that the level of education is an effective factor in the student's satisfaction with the quality of the relationship between him and other colleagues and educational and administrative staff, while the student's satisfaction with the teaching process is influenced by the age of the students.

Tree inventory data from permanent plots in French forest reserves.

We present a data set resulting from the first round of a national monitoring program of forest reserves. It contains 9538 permanent plots, distributed across 111 study sites in mainland France (including Corsica). Notably focusing on dead wood measurement, this protocol has primarily been applied in strict forest reserves and special nature reserves (sensu Bollmann & Braunisch 2013), with 68% (6494) of the plots being currently located in strict forest reserves (unmanaged) and 24.7% (2363 plots) in forests unmanaged for at least 50 years. Sites cover a large variety of ecological conditions, from lowland to subalpine forests, but with an underrepresentation of Mediterranean forests (Table 1). The protocol assesses all the stages of a tree's life cycle, from seedling to decomposed lying dead wood. On each plot, a combination of three sampling techniques was used: (1) fixed-area inventory for regeneration, standing dead trees, living trees, and coarse woody debris (CWD) with diameter over 30 cm; (2) transect lines for CWD with diameter <30 cm; and (3) fixed-angle plot method for living trees with diameter at breast height (DBH) >30 cm (using a relascopic angle of 3%). Measurements include exact tree location (azimuth, distance), species, diameter(s), tree-related microhabitats, decay stage and bark cover, and seedling cover. With ongoing climate change, the program network can also provide important information to monitor changes in forest ecosystems. It can also be used as forest management monitoring or conservation status assessment. These data are freely available for noncommercial scientific use (Creative Commons Attribution 4.0 CC BY SA 4.0) with attribution, and this paper must be cited if this material is reused.

Klinische Forschung im Dienst der Heilkunde: Kontexte, Praxis, Methodik und Theorie des „klinischen Beweises“ von Paul Martini – Beitrag 4: Rezeption, Resonanz und Resümee

Having dealt with Martini's understanding of causality and his procedural elements of evidence in the third part, the concluding article once again takes a historical perspective. It (1) traces the positionings and contexts of Martini’s methodology in a sort of historical longitudinal section and (2) discusses the reasons for the rather reluctant response to his research programme in German and international medicine. We then focus (3) on Martini’s understanding and concept of clinical research, the specific challenges he faced in post-war German medicine – and what remains of it today. Finally, we summarise the key findings of our article series and reflect on Martini’s work in terms of its special nature and significance for clinical medicine in the 20th century.