Miracle-dz/UniFAR-FTUs huggingface dataset:
Predicting Meteorological Variables on Local Level with SARIMA, LSTM and Hybrid Techniques

The choice of holiday destinations is highly depended on climate considerations. Nowadays, since the effects of the climate crisis are being increasingly felt, the need for accurate weather and climate services for hotels is crucial. Such a service could be beneficial for both the future planning of tourists’ activities and destinations and for hotel managers as it could help in decision making about the planning and expansion of the touristic season, due to a prediction of higher temperatures for a longer time span, thus causing increased revenue for companies in the local touristic sector. The aim of this work is to calculate predictions on meteorological variables using statistical techniques as well as artificial intelligence (AI) for a specific area of interest utilising data from an in situ meteorological station, and to produce valuable and reliable localised predictions with the most cost-effective method possible. This investigation will answer the question of the most suitable prediction method for time series data from a single meteorological station that is deployed in a specific location; in our case, in a hotel in the northern area of Crete, Greece. The temporal resolution of the measurements used was 3 h and the forecast horizon considered here was up to 2 days. As prediction techniques, seasonal autoregressive integrated moving average (SARIMA), AI techniques like the long short-term memory (LSTM) neural network and hybrid combinations of the two are used. Multiple meteorological variables are considered as input for the LSTM and hybrid methodologies, like temperature, relative humidity, atmospheric pressure and wind speed, unlike the SARIMA that has a single variable. Variables of interest are divided into those that present seasonality and patterns, such as temperature and humidity, and those that are more stochastic with no known seasonality and patterns, such as wind speed and direction. Two benchmark techniques are used for comparison and quantification of the added predictive ability, namely the climatological forecast and the persistence model, which shows a considerable amount of improvement over the naive prediction methods, especially in the 1-day forecasts. The results indicate that the examined hybrid methodology performs best at temperature and wind speed forecasts, closely followed by the SARIMA, whereas LSTM performs better overall at the humidity forecast, even after the correction of the hybrid to the SARIMA model. Lastly, different hybrid methodologies are discussed and introduced for further improvement of meteorological predictions.
Seismic Performance Evaluation of a Submarine Gas Pipeline

Analyses were conducted on the seismic performance of a proposed offshore gas flowline, which connects a manifold in 830-m water depth to a riser platform in shallow waters of the outer continental shelf. Climbing a 10-degree continental slope, the flowline will be installed on the seafloor underlain by deep carbonate s ediments of sands and silty clays. Two types of analyses were performed for a critical segment of the flowline, where it traverses a narrow ridge flanked by two deep submarine canyons: (1) probabilistic analyses using simplified empirical methods; and (2) deterministic 2D and 3D analyses with FLAC using a nonlinear, effective-stress soil model fully coupled with an empirical pore-pressure generation scheme. Soil properties were derived from PCPT and T-bar data, Bender element tests, and monotonic and cyclic direct simple shear tests. The analysis results indicated an extremely small likelihood of liquefaction along the flowline, with only small deformations predicted to occur for ground motions with a return period of 5,000 years.
Risk factors for cardiovascular events and mortality in patients diagnosed with diffuse large B‐cell lymphoma and treated with anthracyclines

There is an increased risk of congestive heart failure (CHF) following anthracycline‐based chemotherapy in patients with Diffuse Large B‐cell lymphoma (DLBCL). Little is known about risk factors of CHF, other cardiovascular events (CVE), and CVE effect on outcomes. We conducted a retrospective review of 463 newly diagnosed DLBCL patients treated between 2002 and 2016 with anthracycline containing regimens. At a median follow up of 71.3 months, 10.4% patients developed new CHF, 4.97% had new atrial fibrillation and 3.2% had new coronary artery disease. Age over 65, advanced stage DLBCL and diabetes were associated with increased cumulative incidence of CVE. Patients with prior diabetes had decreased progression‐free survival and overall survival in comparison to non‐diabetics. Patients who had a CVE in the first year had significant worse OS then patients who did not have a CVE (Hazard Ratio 10.0, 95% CI, 7.24–13.88). A risk score incorporating age at DLBCL diagnosis, baseline lymphocyte count, disease stage and diabetes stratified into groups with low, intermediate and high risk for CVE, with 1‐year cumulative incidence of CVE of 5.3%, 7.9% and 13.4%. Diffuse large B‐cell lymphoma patients treated with anthracycline containing regimens have high incidence of CVE, which are not limited to CHF. Clinical variables at the time of diagnosis can identify the group of DLBCL patients at highest risk of CVE, for whom preventive interventions should be considered.
Pen shape and size: effects on pig behavior and performance

Crossbred growing pigs, with an average initial weight of 29.9 kg, were housed in groups of 15 in ten experimental pens (five shapes × two sizes) to assess the importance of pen shape in the perception of space quality. Pen sizes provided 0.396 and 0.356 m 2 per pig. In Experiment 1, four replications, each of a 4-week duration, were conducted comparing rectangular (length/width = 3), triangular (equilateral), square and circular pens. In Ex- periment 2, two replications, each of a 2-week duration, were conducted comparing altered circular (circular pen fitted with two 0.5 m interior walls) and square pens. Production parameters (Experiment I only), social behaviors, time budgets and space utilization were monitored for each pen of pigs. Weight gain, feed intake and feed efficiency in Experiment I averaged 623 g day- ~, 1773 g day-~ and 0.353, respectively, and were not affected by pen shape or size. Post-mixing aggression was greater in circular pens than in square pens (34.6 vs 16.8 pig × s spent fight- ing per minute; P<0.01 ) and intermediate in other shapes in Experiment 1. Levels of aggression in altered circular pens did not differ from that in square pens in Experiment 2. Pen shape did not affect levels of aggression or general activity (eating, drinking, standing, lying) in pigs 1 week later. In Experiment 1, pigs in small pens spent more time standing (P< 0.05 ) and tended to have higher protest scores (open-mouthed attack not leading to shoulder pushing; P< 0.06) than pigs in large pens. Defecation areas in all shapes included comers, with pigs in circu- lar pens apparently using feeder edges as corners. In altered circular pens, dunging areas included actual comers. Animals in triangular pens spent more time in quadrants (25% of pen area) containing pen walls (P< 0.001 ) and less time in quadrants farthest from pen walls (P< 0.001 ) than pigs in other shapes. Use of the quadrant of the pen containing pen
The moderating effect of care‐burden on formal caregiver's mental health during COVID‐19

Abstract Background Homecare organisations employ professionals (i.e. gerontologists, nurses, occupational therapists, physiotherapists and social workers) to help their clients gain rights and supervise non‐professional formal caregivers. Formal caregivers, and especially those who work closely with impaired older people, are at greater risk of infecting or being infected by SARS‐Cov‐2 (COVID‐19). During the first waves of COVID‐19, older people were encouraged to stay home; and the care‐burden inflicted on their caregivers has increased. Objectives This study examined formal caregiver's mental health during the COVID‐19 pandemic, that is, the association between anxiety and depression symptoms and how care‐burden moderated this association. Methods A cross‐sectional online survey conducted in the home care services sector throughout Israel. A sample of 400 formal caregivers of older people (Mage = 47.7, SD = 13.8) completed a questionnaire regarding their levels of care‐burden, general anxiety symptoms, and depressive symptoms. Results A significant positive relationship was found between anxiety and depressive symptoms among formal caregivers. The level of care‐burden moderated this relationship, showing that caregivers with higher care‐burden demonstrated a stronger association between anxiety and depressive symptoms. Conclusions Professionals may use ADL/IADL as a practical index to assess care‐burden and the risk of mistreatment. Implications for Practice Formal caregivers with higher care‐burden should get enhanced professional's support to reduce adverse mental health outcomes.
Towards Predictive Crude Oil Purchase: A Case Study in the USA and Europe

Crude oil price volatility impacts the global economy in general, as well as the economies of Europe and the United States in particular; it is supremely difficult to describe its tendency precisely, hence it leads to a forecasting methodology. This study aims to use the autoregressive integrated moving average (ARIMA), and seasonal autoregressive integrated moving average (SARIMA) approaches to cope with this problem in the United States and Europe. The data was gathered from the U.S. Energy Information Administration and federal research economic data (FRED) from January 2017 to September 2021. Simultaneously, values from January 2017 to March 2021, with 51 observations accounting for 90% of the total samples, were employed for the training phase, and the rest were used for the testing phase. The forecast result also indicated that the root mean square error (RMSE) and mean absolute percentage error (MAPE) values, applied by ARIMA models in Europe and the United States, have higher accurate indicators than SARIMA models. As a result, the ARIMA model achieved the best accuracy in both Europe and the USA, with MAPEEurope−ARIMA = 0.05, and MAPEUSA−ARIMA=0.05. Based on these accuracy parameters, the forecasting models appear incredibly reliable; similarly, the study results might assist governing bodies in making significant decisions, thereby accelerating socio-economic development in the world’s two largest economies.
Performance improvement of co‐culture inoculated microbial fuel cell using fuzzy modelling and Harris hawks optimization

Microbial fuel cell (MFC) is a promising technology since two important processes: wastewater treatment and electrical energy, can be obtained simultaneously. The performance of the MFC (maximum power density (MPD) and COD removal) depends mainly on substrate concentration, pH time, and initial COD. Therefore, the main target of this work is to simultaneously increase the MPD and COD removal by determining the optimal controlling parameters. The proposed methodology integrates fuzzy modelling and Harris Hawks optimization (HHO). Firstly, based on the experimental data set, an accurate fuzzy model is created to simulate the performance of MFC in terms of four controlling parameters. To prove the superiority of fuzzy model, the results are compared with response surface methodology (RSM) in terms of RMSE and coefficient of determination (R2). Secondly, using HHO, the optimal values of substrate concentration, co‐culture composition, pH, and time are determined. These four controlling parameters are used as decision variables during the optimization process, whereas the objective function is the simultaneous maximization of the MPD and COD removal. The obtained results proved that the optimal substrate concentration, pH, time, and initial COD values are 58.2%, 7, 14.4 days, and 32 × 10−3 (mg/L) respectively. Under this condition, the integration between fuzzy and HHO, the overall performance of MFC has been improved by 10.37% and 19.13%, respectively, compared with the experimental and RSM.
Hybrid Approach for Facial Expression Recognition Using Convolutional Neural Networks and SVM

Facial expression recognition is very useful for effective human–computer interaction, robot interfaces, and emotion-aware smart agent systems. This paper presents a new framework for facial expression recognition by using a hybrid model: a combination of convolutional neural networks (CNNs) and a support vector machine (SVM) classifier using dynamic facial expression data. In order to extract facial motion characteristics, dense facial motion flows and geometry landmark flows of facial expression sequences were used as inputs to the CNN and SVM classifier, respectively. CNN architectures for facial expression recognition from dense facial motion flows were proposed. The optimal weighting combination of the hybrid classifiers provides better facial expression recognition results than individual classifiers. The system has successfully classified seven facial expressions signalling anger, contempt, disgust, fear, happiness, sadness and surprise classes for the CK+ database, and facial expressions of anger, disgust, fear, happiness, sadness and surprise for the BU4D database. The recognition performance of the proposed system is 99.69% for the CK+ database and 94.69% for the BU4D database. The proposed method shows state-of-the-art results for the CK+ database and is proven to be effective for the BU4D database when compared with the previous schemes.
The Extracellular Matrix Proteins Tenascin-C and Tenascin-R Retard Oligodendrocyte Precursor Maturation and Myelin Regeneration in a Cuprizone-Induced Long-Term Demyelination Animal Model

Oligodendrocytes are the myelinating cells of the central nervous system. The physiological importance of oligodendrocytes is highlighted by diseases such as multiple sclerosis, in which the myelin sheaths are degraded and the axonal signal transmission is compromised. In a healthy brain, spontaneous remyelination is rare, and newly formed myelin sheaths are thinner and shorter than the former ones. The myelination process requires the migration, proliferation, and differentiation of oligodendrocyte precursor cells (OPCs) and is influenced by proteins of the extracellular matrix (ECM), which consists of a network of glycoproteins and proteoglycans. In particular, the glycoprotein tenascin-C (Tnc) has an inhibitory effect on the differentiation of OPCs and the remyelination efficiency of oligodendrocytes. The structurally similar tenascin-R (Tnr) exerts an inhibitory influence on the formation of myelin membranes in vitro. When Tnc knockout oligodendrocytes were applied to an in vitro myelination assay using artificial fibers, a higher number of sheaths per single cell were obtained compared to the wild-type control. This effect was enhanced by adding brain-derived neurotrophic factor (BDNF) to the culture system. Tnr−/− oligodendrocytes behaved differently in that the number of formed sheaths per single cell was decreased, indicating that Tnr supports the differentiation of OPCs. In order to study the functions of tenascin proteins in vivo Tnc−/− and Tnr−/− mice were exposed to Cuprizone-induced demyelination for a period of 10 weeks. Both Tnc−/− and Tnr−/− mouse knockout lines displayed a significant increase in the regenerating myelin sheath thickness after Cuprizone treatment. Furthermore, in the absence of either tenascin, the number of OPCs was increased. These results suggest that the fine-tuning of myelin regeneration is regulated by the major tenascin proteins of the CNS.
A Novel Augmented Reality Mobile-Based Application for Biomechanical Measurement

Human posture and range of motion (ROM) measurements are important health indicators for identifying abnormalities from various disorders (e.g., scoliosis, musculoskeletal disorders, pain syndromes). A viable real-time mobile application for measuring body posture and ROM is currently lacking. To address this need, a novel Android smartphone augmented-reality-based application was developed and evaluated to enable real-time AprilTag2 marker measurement at the point of patient contact (Biomechanical Augmented Reality-Marker, BAR-M). Mobile app performance was evaluated on a body opponent bag (BOB) and 15 healthy participants by comparing smartphone app and Vicon motion analysis output (pelvis, shoulder, arm, torso angles). A Samsung Galaxy smartphone recorded live video, calculated AprilTag orientations and angle of “a line connecting the center of two tags”, and displayed outcomes in real time. For the BOB test, the absolute difference between Vicon and smartphone angles were 0.09° ± 0.05° for hip, 0.09° ± 0.06° for shoulder, and 0.69° for arm abduction. For the participant test, the absolute mean angle differences were 1.70° ± 0.23° for hip, 1.34° ± 0.27° for shoulder, and 11.18° ± 3.68° for arm abduction. Overall, the app obtained valid and reliable angle measurements for postural and ROM assessments using the smartphone’s front camera. Arm abduction results were affected by clothing movement that caused Vicon markers to move differently from AprilTag markers. Thus, with appropriate measurement methods, this real-time smartphone app is a viable tool to facilitate immediate clinical decision making based on human posture and ROM assessments.
Projected Losses of Ecosystem Services Incurred by Reserve Resources of Cultivated Land Development and Development Priority: A Case Study of Linzhou City in Henan Province, China

The development of reserve resources of cultivated land (RRCL) is a vital way of supplementing cultivated land, and plays a crucial role in ensuring food security. However, if we blindly pursue the quantity of development while ignoring the conservation of the ecosystem, we are likely to waste land resources and destroy the ecological environment. Therefore, it is necessary to address the urgent issue of preventing ecological risks resulting from the development of RRCL and to enhance the actual effect of supplementing cultivated land. Taking Linzhou City in Henan Province as an example, this paper first assessed the tillability of RRCL and estimated the functionality of ecosystem services. Then it projected the losses of ecosystem services incurred by RRCL development, based on which it determined the development priority. The following conclusions were drawn: (1) The total area of RRCL in Linzhou City amounts to 8845 hectares. (2) According to the research forecast, the total annual losses of ecosystem services incurred by RRCL development in Linzhou City include: water conservation of 776,200 m3, soil retention of 340.84 t, and carbon sequestration and oxygen release of 2311.12 t. Moreover, the total value of losses amounts to RMB 15.7754 million. (3) The ecological losses incurred by RRCL development vary with the different types of land. Overall, the ecological loss derived from reclaimable land is inferior to that of cultivable land, with the average value of ecological loss amounting to RMB 600 and RMB 5300 per hectare, respectively. The ecological loss from the development of class II land is: pond < garden land < artificial grassland < artificial forest land < natural grassland < bare land. Moreover, land development should be postponed when the quantity of ecological losses reaches level III or higher. (4) Corrections are made based on the ecological coefficient of the economic potential of RRCL development so as to determine the priority of development. The research findings indicate that the priority of development of eastern towns is higher than that of central and western towns in Linzhou City, with Donggang and Hengshui topping the priority list and Shibanyan, Lingyang, and Chengguan having the lowest priority.
Natural product‐based nanomedicine applied to fungal infection treatment: A review of the last 4 years

Fungal infections are one of the main public health problems, especially in immunocompromised patients, nosocomial environments, patients with chronic diseases, and transplant recipients. These diseases are increasingly frequent and lethal because the microorganism has a high capacity to acquire resistance to available therapy. The main resistance factors are the emergence of new strains and the uncontrolled use of antifungals. It is, therefore, important to develop new methods that contribute to combating fungal diseases in the clinical area. Natural products have considerable potential for the development of new drugs with antifungal activity, mainly due to their biocompatibility and low toxic effect. This promising antimicrobial activity of natural products is mainly due to the presence of flavonoids, terpenes, and quinones, which explains their antifungal potential. Pharmaceutical nanotechnology has been explored to enhance the delivery, selectivity, and clinical efficacy of these products. Nanotechnological systems provide a safe and selective environment for various substances, such as natural products, improving antifungal activity. However, further safety experiments (in vivo or clinical trials) need to be carried out to prove the therapeutic action of natural products, since they may have undesirable, toxic, and mutagenic effects. Therefore, this review article addresses the main nanotechnological methods using natural products for effective future treatment against the main fungal diseases.
Dielectric Properties of Hydrothermally Modified Potato, Corn, and Rice Starch

The effect of starch granule sizes, shapes, composition, and frequency on the dielectric properties (dielectric constant, loss factor, and conductivity) of native and hydrothermally modified starches (potato, corn, and rice starch) are investigated in this work. Dielectric properties are determined from 5 Hz to 5 GHz. The modified starches exhibit lower dielectric properties than the native starches from 5 Hz to 5 GHz due to the disruption of the native polysaccharide’s molecular arrangement. The modified potato starch shows the highest loss factor (208.12 at 50 Hz and 19.95 at 500 Hz) and stable conductivity (~5.33 × 10−7 S/m at 50 Hz and 500 Hz) due to the larger continuous network structure after hydrothermal modification. The rice starch shows the largest difference in dielectric constant (47.30%) and loss factor (71.42%) between the modified form and native form in the frequency range of 5 MHz–5 GHz. This is due to the restriction of dipole motions in the closely packed structure after hydrothermal modification. The findings indicate that the quality of starch modification can be characterized by dielectric properties for assisting starch-based plastic production’s design.
Enzymatic glycan remodeling–metal free click (GlycoConnect™) provides homogenous antibody-drug conjugates with improved stability and therapeutic index without sequence engineering

ABSTRACT Antibody-drug conjugates (ADCs) are increasingly powerful medicines for targeted cancer therapy. Inspired by the trend to further improve their therapeutic index by generation of homogenous ADCs, we report here how the clinical-stage GlycoConnect™ technology uses the globally conserved N-glycosylation site to generate stable and site-specific ADCs based on enzymatic remodeling and metal-free click chemistry. We demonstrate how an engineered endoglycosidase and a native glycosyl transferase enable highly efficient, one-pot glycan remodeling, incorporating a novel sugar substrate 6-azidoGalNAc. Metal-free click attachment of an array of cytotoxic payloads was highly optimized, in particular by inclusion of anionic surfactants. The therapeutic potential of GlycoConnect™, in combination with HydraSpace™ polar spacer technology, was compared to that of Kadcyla® (ado-trastuzumab emtansine), showing significantly improved efficacy and tolerability. Graphical Abstract