Miracle-dz/UniFAR-FTUs huggingface dataset:
Water-redispersible cellulose nanocrystals adsorption of glucose via alcohol precipitation

Abstract Cellulose nanocrystals (CNCs) are difficult to redisperse in water after completely dried due to their irreversible agglomeration during drying. Various alternatives have been proposed in the literature, some of which require energy-intensive methods of redispersion or might use an additive that is inadequate or toxic for food and pharmaceutical-related applications. The present work examined a novel approach that involved using glucose as redispersing agents to redisperse CNCs. The experimental data indicated that glucose could be adsorbed onto the surface of CNCs through alcohol precipitation. The oven-dried CNCs, which were adsorbed with glucose via alcohol precipitation, could be homogeneously redispersed in water. The water-redispersed CNCs showed similar particle size distribution and zeta potential to those of the CNCs without drying. GRAPHICAL ABSTRACT
Impaired fertility in men diagnosed with inflammatory arthritis: results of a large multicentre study (iFAME-Fertility)

Objectives The impact of inflammatory arthritis (IA) on male fertility remains unexplored. Our objective was to evaluate the impact of IA on several male fertility outcomes; fertility rate (number of biological children per man), family planning, childlessness and fertility problems. Methods We performed a multicentre cross-sectional study (iFAME-Fertility). Men with IA 40 years or older who indicated that their family size was complete were invited to participate. Participants completed a questionnaire that included demographic, medical and fertility-related questions. To analyse the impact of IA on fertility rate, patients were divided into groups according to the age at the time of their diagnosis: ≤30 years (before the peak of reproductive age), between 31 and 40 years (during the peak) and ≥41 years (after the peak). Results In total 628 participants diagnosed with IA were included. Men diagnosed ≤30 years had a lower mean number of children (1.32 (SD 1.14)) than men diagnosed between 31 and 40 years (1.60 (SD 1.35)) and men diagnosed ≥41 years (1.88 (SD 1.14)). This was statistically significant (p=0.0004). The percentages of men diagnosed ≤30 and 31–40 years who were involuntary childless (12.03% vs 10.34% vs 3.98%, p=0.001) and who reported having received medical evaluations for fertility problems (20.61%, 20.69% and 11.36%, p=0.027) were statistically significant higher than men diagnosed ≥41 years. Conclusions This is the first study that shows that IA can impair male fertility. Men diagnosed with IA before and during the peak of reproductive age had a lower fertility rate, higher childlessness rate and more fertility problems. Increased awareness and more research into the causes behind this association are urgently needed.
Global palliative care research (2002-2020): bibliometric review and mapping analysis

Background and objective Despite the important benefits of a bibliometric approach on mapping a research field, relatively little efforts have previously been conducted to map and analyse the global trends of palliative care (PC)-related research. This bibliometric review aimed to provide an overall picture and systematic mapping of the state of research trends within the field of PC internationally. Methods Scopus and Web of Science databases were searched to retrieve original articles focusing on PC between 2002 and 2020. Searching was conducted on 5 May 2020, and was updated on 6 May 2021. All retrieved articles were assessed by title and abstract, and the bibliometric metadata of those that met the inclusion criteria were downloaded for analysis. The results were analysed by VOSviewer and Gephi software. Results A total of 19,199 articles met the inclusion criteria. Significant growth of the number of published articles was reported by around five-fold from 2002 to 2020. The USA and UK were the most productive countries in terms of the number of papers published and citations. Weak collaborations were observed between low-income or middle-income countries and high-income countries. Cancer-related PC research was the most common focus. Seven clusters of research were identified and included heart failure and cancer prognosis, nursing home, pain and symptoms management, PC knowledge and attitudes, quality improvement of services, PC ethics, and the ongoing assessment of PC services. Conclusions There is a need to expand PC-related research to non-cancer diseases. More international research and cross-institutional cooperation is required to address more global PC issues and benefit from wider sharing of expertees, potentially leading to higher quality or more impactful studies. Setting up research agendas and priorities from funding bodies and institutions may also enhance cooperation among researchers.
Coyote: A Dataset of Challenging Scenarios in Visual Perception for Autonomous Vehicles

Recent advances in Artiﬁcial Intelligence have immense potential for the realization of self-driving applications. In particular, deep neural networks are being applied to object detection and semantic segmentation, to support the operation of semi-autonomous vehicles. While full Level 5 autonomy is not yet available, elements of these technologies are being brought to market in advanced driver assistance systems that provide partial automation at Level 2 and 3. However, multiple studies have demonstrated that current state-of-the-art deep learning models can make high-conﬁdence but incorrect predictions. In the context of a critical application such as understanding the scene in front of a vehicle, which must be robust, accurate and in real-time, such failures raise concerns; most signiﬁcantly, they may pose a substantial threat to the safety of the vehicle’s occupants and other people with whom the vehicle shares the road. To examine the challenges of current computer vision approaches in the context of autonomous and semi-autonomous vehicles, we have created a new test dataset, called Coyote 1 , with photographs that can be understood correctly by humans but might not be successfully parsed by current state-of-the-art image recognition systems. The dataset has 894 photographs with over 1700 ground-truth labels, grouped into 6 broad categories. We have tested the dataset against existing state-of-the-art object detection (YOLOv3 & Faster R-CNN) and semantic segmentation (DeepLabv3) models to measure the models’ performance and identify situations that might be a source of risk to transportation safety. Our results demonstrate that these models can be confused for various adversarial examples resulting in lower performance
Anthocyanins Content in Blueberries ( Vaccinium corymbosum L.) in Relation to Freesing Duration

The changes of total anthocyanins (TA) content in fruit of blueberries in relation to freezing duration are the aim of this study. The samples of 21 chosen cultivars obtained from the research breed station were stored in polyethylene bags in freezing box at temperature -18°C. In ethanolic blueberry extracts TA contents were by spec - trophotometric method during the time of 6 months at period of 3 months determined. Significant differences of TA content among the observed cultivars were confirmed. The value interval was 615.8-3206.3 mg/kg. The average TA content in 10 very early, resp. early cultivars was 1655.8 mg/kg, in 5 medium early cultivars 1515.6 mg/kg, in 6 medium late, resp. late cultivars 1431.2 mg/kg. During 6 months of blueberries store in the freezing box the average decrease 16.7% of TA content was observed. The average decrease of TA content in very early, resp. early cultivars was 19.6%, in medium early cultivars 16.5% and in medium late, resp. late cultivars 14%.
Extractive Summarization for Explainable Sentiment Analysis using Transformers

In recent years, the paradigm of eXplainable Artificial Intelligence (XAI) systems has gained wide research interest and beyond. The Natural Language Processing (NLP) community is also approaching this new way of understanding AI applications: building a suite of models that provide an explanation for the decision, without affecting performance. This is certainly not an easy task, considering the wide use of very poorly interpretable models such as Transformers, which in recent years are found to be almost ubiquitous in the NLP literature because of the great strides they have allowed. Here we propose two different methodologies to exploit the performance of these models in a task of sentiment analysis and, in the meantime, to generate a summary that serves as an explanation of the decision taken by the system. To compare the classification performance of the two methodologies, we used the IMDB dataset while, to assess the explainability performance, we annotated some samples of this dataset to retrieve human extractive summaries, benchmarking them with the summaries generated by the systems.
Epistemic Defenses against Scientific and Empirical Adversarial AI Attacks

In this paper, we introduce “scientiﬁc and empirical adversarial AI attacks” (SEA AI attacks) as umbrella term for not yet prevalent but technically feasible deliberate malicious acts of speciﬁcally crafting AI-generated samples to achieve an epistemic distortion in (applied) science or engineering contexts. In view of possible socio-psycho-technological impacts, it seems responsible to pon-der countermeasures from the onset on and not in hindsight. In this vein, we consider two illustrative use cases: the example of AI-produced data to mis-lead security engineering practices and the conceivable prospect of AI-generated contents to manipulate scientiﬁc writing processes. Firstly, we contextualize the epistemic challenges that such future SEA AI attacks could pose to society in the light of broader i.a. AI safety , AI ethics and cybersecurity-relevant efforts. Secondly, we set forth a corresponding supportive generic epistemic defense approach. Thirdly, we effect a threat modelling for the two use cases and propose tailor-made defenses based on the foregoing generic deliberations. Strik-ingly, our transdisciplinary analysis suggests that employing distinct explanation-anchored , trust-disentangled and adversarial strategies is one possible principled complementary epistemic defense against SEA AI attacks – albeit with caveats yielding incentives for future work.
Curriculum learning for scene text recognition

Abstract. Scene text recognition (STR) is a challenging computer vision task. Recent progress has been made on developing a complex network to increase recognition accuracy. Most STR algorithms focus on improving the network structure and correcting slanted text to improve the accuracy of text recognition. Inspired by the concept of curriculum learning, we applied this method to the field of text recognition. We propose an easy-to-implement method that improves the accuracy of text recognition using the concept of curriculum learning. Taking into account the specific characteristics of text, we propose defining the difficulty of scene images from both the human perspective and the machine perspective. The key idea of the proposed method is to guide the training process to begin with training simple samples and progressively increase the complexity of the training samples. Experimental results demonstrate that the proposed method effectively accelerates the convergence and improves the accuracy of text recognition.
Applying Strategic Reasoning for Accountability Ascription in Multiagent Teams

For developing human-centred trustworthy autonomous systems and ensuring their safe and ef-fective integration with the society, it is crucial to enrich autonomous agents with the capacity to represent and reason about their accountability. This is, on one hand, about their accountability as col-laborative teams and, on the other hand, their individual degree of accountability in a team. In this context, accountability is understood as being responsible for failing to deliver a task that a team was allocated and able to fulﬁl. To that end, the semantic (strategic reasoning) machinery of the Alternating-time Temporal Logic (ATL) is a natural modelling approach as it captures the temporal, strategic, and coalitional dynamics of the notion of accountability. This allows focusing on the main problem on: “Who is accountable for an un-fulﬁlled task in multiagent teams: when, why, and to what extent? ” We apply ATL-based semantics to deﬁne accountability in multiagent teams and de-velop a fair and computationally feasible procedure for ascribing a degree of accountability to involved agents in accountable teams. Our main results are on decidability, fairness properties, and computational complexity of the presented accountability ascription methods in multiagent teams.
Comparative Analysis of Prepectoral versus Subpectoral Implant-based Breast Reconstruction

Background: Recent advances in mastectomy and reconstruction have allowed for an evolution in implant-based breast reconstruction to a muscle-sparing, prepectoral approach. Advantages of this technique may include reductions in postoperative pain, shorter hospitalization, less narcotic usage, and improved aesthetic outcomes. Postoperative complication rates are described as comparable to subpectoral techniques; however, little comparative data exist to adequately assess prepectoral versus subpectoral implant placement. Methods: To address this knowledge gap, we performed a single institution retrospective review of 186 (83 prepectoral, 103 subpectoral) consecutive immediate breast reconstructions. All cases were tracked for a minimum of 2 years between 2016 and 2021. Results: Prepectoral patients demonstrated an overall higher seroma rate (P = 0.001), with all other postoperative complications being comparable. Prepectoral patients tolerated higher intraoperative tissue expander fill volumes (P < 0.001), shorter hospital stays (P = 0.007), fewer clinic visits for tissue expansion (P < 0.001), and experienced less animation deformity (P = 0.005). Both groups demonstrated similar pain scores (P = 0.65) and needs for narcotics (P = 0.8) as well as comparable scores of capsular contracture (P = 0.791). Conclusions: Our comparative analysis of consecutive immediate implant-based breast reconstructions finds prepectoral reconstruction to be safe and effective. Compared with subpectoral reconstruction, the prepectoral approach may offer quicker tissue expansion, less postoperative office visits, less need for muscle relaxants, and a shorter hospital stay with a comparable complication profile.
THE ROLE OF INFRASTRUCTURE IN PROMOTING DOMESTIC INVESTMENT IN PAKISTAN

Infrastructure is an umbrella term used for many activities, as it plays vital role for industrial and overall economic activities. The study examines the historical trends of GDP, infrastructure and investment in Pakistan. The study investigates the empirical impacts of infrastructure on domestic investment from 1975 to 2013. Variables included in the study are gross fixed capital formation, telephone lines, length of roads, inflation, GDP and interest rate; and the ARDL model is applied for estimation of empirical results. These results found the impact of infrastructure on domestic investment which has positive and significant effect. However, telephone lines variable remain insignificant during long-run, while it is significant in the short-run. The study also finds positive and significant relation between the domestic investment and GDP. The impact of interest rate and inflation is negative and significant during short-run on domestic investment but, the impact of inflation remains insignificant during long-run. The findings suggest that special attention should be paid towards infrastructure along with other variables, while formulating investment policies.
Comparison of Rasch Model Logits and Likert Mean Score in Testing the Normality Assumption

The lack of empirical evidence about Rasch model logits as a potential score in normality testing boost the motivations on how this type of data can replace the Likert mean score. The research also would like to see how these logits will be variant by fixing the diversity of zones selected for Adversity Quotient (AQ) measurement. The AQ was tested using IKBAR (Instrumen Kecerdasan Menghadapi Cabaran) with CORE model (Control, Ownership, Reach and Endurance) on 1845 polytechnic students from five different zones in Malaysia using a proportionate stratified multistage cluster sampling. The findings revealed that the skewness and kurtosis pattern for all zones showed that Rasch model logits are greater than the Likert mean score. The gaps pattern showed that Borneo dominated the largest gap for Control and AQ for both skewness and kurtosis. In terms of skewness, North region dominated the Endurance gap and the West dominated the Reach gaps. The East dominated the kurtosis gaps for Reach and Endurance. The Rasch model logits for all zones generally had a probability of failing to meet the normality acceptance range. A paired-samples t-test revealed that there was a significant difference for both scores. There was a significant average difference between both score. Rasch model logits were higher than Likert mean score. Based on the results, it is clear that the patterns of the Rasch model logits applicability exposed a great potential and alternative to be used by the researchers as normality data testing besides the Likert mean score. Further studies are proposed to be carried out to explore the potential of using logits for different settings and to ensure applicability to the other normality testing for educational research.
Naturalista sicil., S. IV, XLIV (1-2), 2020, pp. 289-294 BREVI NOTE / SHORT NOTES

Insect seasonality is mainly controlled by three factors: resource availability, temperature and rainfall (WOLDA, 1978). Concerning the dung beetles, one of the larger and hyper-diverse groups of insects, seasonality has strong effect on their activity (CAMBEFORT, 1991) and phenology is an important factor in structuring their assemblages, at least in temperate regions (WASSMER, 1994). In the Mediterranean region, dung beetles have usually a peak of activity in spring, while another smaller peak occurs in autumn (see LUMARET & KIRK, 1987, 1991; GALANTE et al., 1995). However, their occurrence and abundance may be influenced also by the lack of rain in midsummer and the low temperatures in midwinter (RIDSDILL-SMITH & HALL, 1984). Within this geographical context, structure and phenology of dung beetle communities have been studied mostly on continental areas (see for instance LUMARET & KIRK, 1987; ROMERO-ALCARAZ & ÁVILA, 2000; HALOTI et al., 2006; JAY-ROBERT et al., 2008; ERROUISSI et al., 2009; AGOGLITTA et al., 2012), while only few data are available for island environments (LOBO & MARTÍN-PIERA, 1993). The aim of this study is to evaluate the changes in the structure and diversity of dung beetle assemblages in a small Mediterranean island through a year.
Trophic relationships among fourteen native and non-native fish species in the Shatt Al-Arab River, Iraq

The present study objectified to evaluate the trophic relationships among 14 fish species (10 natives and 4 non-natives) in the Shatt Al-Arab River, considering the trophic niche breadth and the diet overlaps of the species. The food items in the stomach of each species are determined by adopting the index of relative importance (IRI). The dietary analysis revealed a total of 12 types of major food items consumed (which represent >10% IRI). Two species (Oreochromis aureus and Cptodon zillii) were herbivores consumed mostly macrophytes, algae and diatoms. Four species (Planiliza abu, P. klunzengeri, P. subviridis and Osteomugil speigleri) were herbivores mainly fed on diatoms, macrophytes, detritus and algae. Three species (Carasobarbus luteus, Carassius auratus and Cyprinus carpio) were omnivores mostly consumed macrophytes, detritus, diatoms and algae. Two species (Tenualosa illisha and Nematalosa nasus) were filter feeders fed largely on zooplankton, algae, detritus and macrophytes. Three species (Acanthopagrus arabicus, Johnius belangerii and J. dussumeiri) were carnivores mainly preyed on shrimps, crabs and fish. Levin’s index diet breadth analyses divided the studied fish species into three categories; two species with high specialization, five species with low specialization, and seven species with generalization feeders. The dietary composition of fish species exhibited 62 diet overlaps as indicated by the Jaccard index, eight of them high, 36 moderate and 18 low overlaps. Only J. dussumeiri and J. belangerii have no diet overlap with other species. Overall, the study demonstrates that most trophic overlaps between species were moderate, but high degree overlap was between the native species (C. luteus) and invading species (C. auratus) and therefore strengthen earlier conclusions regarding interspecific competition between these two species.
Industry Self-regulation

One potential list of candidates starts with the world‘s top 100 economies. The list begins with some familiar names –the European Union, the United States, China, and Brazil. Certainly all will have a role to play, but one can easily envision barriers each might face. Then somewhere around the 12th rank an odd thing occurs: the names shift from those of nations to those of corporations. For the remainder of the list, corporations become common. In fact, about half of the top ―economies‖ in the world are private corporations. Some of the comparisons are staggering. Exxon‘s revenues are larger than Australia‘s GDP, Volkswagen‘s bigger than Pakistan‘s, Costa Rica‘s economy smaller than that of Lowes‘.
Investigated Performance of Okumura-Hata Model For Dvb-T2 Signal Propagation In Nigeria

The choice of signal propagation model in the implementation and analysis of the digital terrestrial television broadcast (DTTB) signal performance level in the Telecommunication Industry remains pivotal to Engineers and Scientists. The success recorded in the design and implementation of any DTTB system is attributed to the choice of the predicting model adopted. The aim of this investigation is to establish the efficacy of Okumura-Hata path-loss model in the application of DTTB network in Nigeria. The measured path-loss was relatively investigated with respect to Okumura-Hata and Free space propagation model using a simple drive test methodology. The Okumura-Hata model offered considerable RMSEs closer to zero which is satisfactory for high performance in terms of received signal strength when compared to the other propagation model. However, it implies that Okumura-Hata model could be preferred in the planning, design and implementation of DTTB network in Nigeria due to its superior performance in the predicted signal strength using digital video broadcast –terrestrial (second generation - DVB-T2) technology.