The start-up sector in Romania, particularly in the North-West Development Region (NW), is experiencing rapid growth and driving innovation and economic development. Understanding this sector and its connection to Research and Development (R&D) is vital for regional progress. The NW Region has become a prominent hub for start-up activity in Romania. Examining the start-up sector in these regions is essential as it contributes significantly to economic growth. Start-ups introduce disruptive technologies, create new market opportunities, and promote regional diversification. The impact of the R&D sector on economic growth cannot be underestimated. R&D activities drive innovation, laying the groundwork for the emergence and success of start-ups. Investing in R&D fosters knowledge creation, technological advancements, and intellectual property, which are crucial for entrepreneurial ventures. By understanding the interplay between start-ups and the R&D sector, stakeholders can develop targeted strategies for fostering innovation-driven economic growth. This article aims to provide valuable insights into the start-up sector in Romania's NW Region, its relationship with R&D, and the connection between total expenditure on R&D and economic growth in both Romania and the NW Region.

BACKGROUND Autofluorescence (AF) - Raman spectroscopy is a technology that can detect residual basal cell carcinoma (BCC) on the resection margin of fresh surgically excised tissue specimens. The technology does not require tissue fixation, staining, labelling, or sectioning, and provides quantitative diagnosis maps of the surgical margins in 30 minutes. OBJECTIVES To determine the accuracy of the AF-Raman instrument to detect incomplete excisions of BCC during Mohs micrographic surgery, using histology as reference standard. METHODS Skin layers from 130 patients undergoing Mohs surgery at the Nottingham University Hospitals NHS Trust (September 2022 to July 2023) were investigated with the AF-Raman instrument. The layers were measured fresh, immediately after excision. The AF-Raman results and the intra-operative assessment by Mohs surgeons were compared to a post-operative consensus-derived reference produced by three dermatopathologists. The sensitivity, specificity, positive predictive value, and negative predictive value were calculated. RESULTS The AF-Raman analysis was successfully completed for 125 out of the 130 layers. The AF-Raman analysis covered 91% of the specimen surface area on average, with the lowest being 87% for eyelid and the highest being 94% for forehead specimens. The AF-Raman instrument identified positive margins in 24 out of 36 BCC-positive cases, resulting in a 67% sensitivity (95% confidence intervals (CI): 49%-82%) and negative margins in 65 out of 89 BCC-negative cases, resulting in a 73% specificity (95% CI 63%-82%). Only one out of the 12 false negative cases was caused by misclassification by the AF-Raman algorithm. The other 11 false negatives cases were produced because no valid Raman signal was recorded at the location of the residual BCC due to either occlusion by blood or poor contact between tissue and cassette window. The intra-operative diagnosis by Mohs surgeons identified positive margins in 31 out of 36 BCC-positive cases, 86% sensitivity (95% CI: 70%-95%), and negative margins in 79 out of 89 BCC-negative cases, 89% specificity (95% CI: 81%-95%). CONCLUSIONS This study shows that the AF-Raman instrument has potential for intra-operative microscopic assessment of surgical margins in surgery of BCC. Further improvements are required for tissue processing to ensure complete coverage of the surgical specimens. ClinicalTrials.gov ID NCT03482622.

The choices made by autonomous robots in social settings bear consequences for humans and their presumptions of robot behavior. Explanations can serve to alleviate detrimental impacts on humans and amplify their comprehension of robot decisions. We model the process of explanation generation for robot navigation as an automated planning problem considering different possible explanation attributes. Our visual and textual explanations of a robot’s navigation are influenced by the robot’s personality. Moreover, they account for different contextual, environmental, and spatial characteristics. We present the results of a user study demonstrating that users are more satisfied with multimodal than unimodal explanations. Additionally, our findings reveal low user satisfaction with explanations of a robot with extreme personality traits. In conclusion, we deliberate on potential future research directions and the associated constraints. Our work advocates for fostering socially adept and safe autonomous robot navigation.

Product design and manufacturing leverage 3D scanning for various applications. This study aims to investigate the effectiveness of 3D scanning in furniture production by surveying the literature and showcasing four real-world case studies. The literature review reveals that 3D data acquired from real-world objects have applications in research, rapid prototyping, restoration, and preservation of antique furniture, optimizing CNC machining processes, and measuring furniture components for quality control. The case study descriptions demonstrated the circumstances, rationale, and methodology for 3D scanning. All the case studies analyzed stem from the collaboration between the Laboratory for Product Development and Design at the Faculty of Mechanical Engineering at the University of Sarajevo and various furniture production enterprises from Bosnia and Herzegovina. The conclusions highlight that 3D scanning in the furniture sector is advantageous for developing computer-aided design models from early-stage design prototypes, validating the dimensional accuracy of manufactured components by comparing with CAD models, safeguarding and reconstructing vintage furniture, and remanufacturing formerly produced goods that lack complete technical records (reverse engineering).

Highlights • Gene expression in response to Cd: The study analyzed the expression levels of several genes (RAMP6, HIPP26, HIPP27, HMA2, and MAPK2) in response to CdCl2 exposure. The results showed an overall increase in gene expression with higher Cd concentrations, except for HMA2 at 1000 µM CdCl2.• MAPK2 expression variability: The expression of MAPK2 varied among kale varieties, with an overall decrease in Kale 23. This may be due to mutations in the MAPK2 primers and potential cell death in higher CdCl2 concentrations.• Role of RAMP6: RAMP6 was found to have a proportional increase in expression with increasing CdCl2 concentrations, suggesting its role in Cd metabolism in B. Oleracea.• HIPP26 and HIPP27 Potential Roles: While studies specific to B. Oleracea are lacking, findings from A. thaliana suggest that HIPP26 and HIPP27 may be involved in Cd influx in B. Oleracea, with HIPP27 possibly playing a role in Cd detoxification.• Kale varietal resistance: Domestic B. Oleracea kale varieties exhibited greater resistance to Cd stress compared to hybrid varieties, highlighting the potential for phytoremediation.

External Human-Machine Interfaces (eHMIs) have been evaluated to facilitate interactions between Automated Vehicles (AVs) and pedestrians. Most eHMIs are, however, visual/ light-based solutions, and multi-modal eHMIs have received little attention to date. We ran an experimental video study (<Formula format="inline"><TexMath><?TeX $N~=~29$?></TexMath><AltText>Math 1</AltText><File name="chi24-142-inline1" type="svg"/></Formula>) to systematically understand the effect on pedestrian’s willingness to cross the road and user preferences of a light-based eHMI (light bar on the bumper) and two sound-based eHMIs (bell sound and droning sound), and combinations thereof. We found no objective change in pedestrians’ willingness to cross the road based on the nature of eHMI, although people expressed different subjective preferences for the different ways an eHMI may communicate, and sometimes even strong dislike for multi-modal eHMIs. This shows that the modality of the evaluated eHMI concepts had relatively little impact on their effectiveness. Consequently, this lays an important groundwork for accessibility considerations of future eHMIs, and points towards the insight that provisions can be made for taking user preferences into account without compromising effectiveness.

The selection of handling equipment represents an important aspect of operational planning in logistics centers and affects the potential increase in work efficiency. Therefore, it is necessary to consider various factors when making decisions regarding the selection of handling equipment. This paper presents the selection of an electric forklift for the needs of loading and handling activities in a closed warehouse of the GTC (Goods Transport Center) Doboj. An MCDM model, consisting of FUCOM (Full Consistency Method) and MARCOS (Measurement of Alternatives and Ranking According to the COmpromise solution) was applied to evaluate electric forklifts. The FUCOM method was used to determine the values of criteria, and the MARCOS method was used to evaluate electric forklifts. After obtaining the results, sensitivity analysis and comparative analysis were performed.

Abstract Introduction Post-kala-azar dermal leishmaniasis (PKDL) arises as a dermal complication following a visceral leishmaniasis (VL) infection. Current treatment options for PKDL are unsatisfactory, and there is a knowledge gap regarding the distribution of antileishmanial compounds within human skin. The present study investigated the skin distribution of miltefosine in PKDL patients, with the aim to improve the understanding of the pharmacokinetics at the skin target site in PKDL. Methods Fifty-two PKDL patients underwent treatment with liposomal amphotericin B (20 mg/kg) plus miltefosine (allometric dosing) for 21 days. Plasma concentrations of miltefosine were measured on study days 8, 15, 22 and 30, while a punch skin biopsy was taken on day 22. A physiologically based pharmacokinetic (PBPK) model was developed to evaluate the distribution of miltefosine into the skin. Results Following the allometric weight-based dosing regimen, median miltefosine concentrations on day 22 were 43.73 µg/g (IQR: 21.94–60.65 µg/g) in skin and 33.29 µg/mL (IQR: 25.9–42.58 µg/mL) in plasma. The median individual concentration ratio of skin to plasma was 1.19 (IQR: 0.79–1.9). In 87% (45/52) of patients, skin exposure was above the suggested EC90 PK target of 10.6 mg/L associated with in vitro susceptibility. Simulations indicated that the residence time of miltefosine in the skin would be more than 2-fold longer than in plasma, estimated by a mean residence time of 604 versus 266 hours, respectively. Conclusion This study provides the first accurate measurements of miltefosine penetration into the skin, demonstrating substantial exposure and prolonged retention of miltefosine within the skin. These findings support the use of miltefosine in cutaneous manifestations of leishmaniasis. In combination with parasitological and clinical data, these results are critical for the future optimization of combination therapies with miltefosine in the treatment of PKDL.

This article is linked to Aliu et al papers. To view these articles, visit https://doi.org/10.1111/apt.17988 and https://doi.org/10.1111/apt.18027.

Objective. This study develops a deep learning (DL) method for fast auditory attention decoding (AAD) using electroencephalography (EEG) from listeners with hearing impairment (HI). It addresses three classification tasks: differentiating noise from speech-in-noise, classifying the direction of attended speech (left vs. right) and identifying the activation status of hearing aid noise reduction algorithms (OFF vs. ON). These tasks contribute to our understanding of how hearing technology influences auditory processing in the hearing-impaired population. Approach. Deep convolutional neural network (DCNN) models were designed for each task. Two training strategies were employed to clarify the impact of data splitting on AAD tasks: inter-trial, where the testing set used classification windows from trials that the training set had not seen, and intra-trial, where the testing set used unseen classification windows from trials where other segments were seen during training. The models were evaluated on EEG data from 31 participants with HI, listening to competing talkers amidst background noise. Main results. Using 1 s classification windows, DCNN models achieve accuracy (ACC) of 69.8%, 73.3% and 82.9% and area-under-curve (AUC) of 77.2%, 80.6% and 92.1% for the three tasks respectively on inter-trial strategy. In the intra-trial strategy, they achieved ACC of 87.9%, 80.1% and 97.5%, along with AUC of 94.6%, 89.1%, and 99.8%. Our DCNN models show good performance on short 1 s EEG samples, making them suitable for real-world applications. Conclusion: Our DCNN models successfully addressed three tasks with short 1 s EEG windows from participants with HI, showcasing their potential. While the inter-trial strategy demonstrated promise for assessing AAD, the intra-trial approach yielded inflated results, underscoring the important role of proper data splitting in EEG-based AAD tasks. Significance. Our findings showcase the promising potential of EEG-based tools for assessing auditory attention in clinical contexts and advancing hearing technology, while also promoting further exploration of alternative DL architectures and their potential constraints.

Abstract Chromium (Cr) toxicity, even at low concentrations, poses a significant health threat to various environmental species. Cr is found in the environment in two oxidation states that differ in their bioavailability and toxicity. While Cr(III) is essential for glucose metabolism, the oxyanion chromate Cr(VI) is mostly of anthropogenic origin, toxic, and carcinogenic. The sources of Cr in the environment are multiple, including geochemical processes, disposal of industrial waste, and industrial wastewater. Cr pollution may consequently impact the health of numerous plant and animal species. Despite that, the number of published studies on Cr toxicity across environmental species remained mainly unchanged over the past two decades. The presence of Cr in the environment affects several plant physiological processes, including germination or photosynthesis, and consequently impacts growth, and lowers agricultural production and quality. Recent research has also reported the toxic effects of Cr in different aquatic and terrestrial organisms. Whereas some species showed sensitivity, others exhibited tolerance. Hence, this review discusses the understanding of the ecotoxicological effect of Cr on different plant and animal groups and serves as a concise source of consolidated information and a valuable reference for researchers and policymakers in an understanding of Cr toxicity. Future directions should focus on expanding research efforts to understand the mechanisms underlying species-specific responses to Cr pollution. Graphical Abstract

Anonymous communication networks (ACNs) enable Internet browsing in a way that prevents accessed content from being traced back to the user. This provides a high level of privacy, protecting individuals from being tracked by advertisers, governments, and other entities. The Tor network, a prominent example of such a network, uses a layered encryption scheme to encapsulate data packets, employing Tor nodes to obscure the routing process before the packets enter the public Internet. While Tor is capable of providing substantial privacy, its encryption relies on schemes such as RSA and Diffie-Hellman for distributing symmetric keys, which are vulnerable to quantum computing attacks and are currently in the process of being phased out. To overcome this threat, we propose a quantum resistant alternative to RSA and Diffie-Hellman for distributing symmetric keys, namely, quantum key distribution (QKD). Standard QKD networks depend on trusted nodes to relay keys across long distances. However, reliance on trusted nodes in the quantum network does not meet the criteria necessary for establishing a Tor circuit in the ACN. We address this issue by developing a protocol and network architecture that integrates QKD without the need for trusted nodes, thus meeting the requirements of the Tor network and creating a quantum secure anonymous communication network.