AI Meets the Shopper: Psychosocial Factors in Ease of Use and Their Effect on E-Commerce Purchase Intention.

The evolution of e-retail and the contribution of artificial intelligence in improving algorithms for greater customer engagement highlight the potential of these technologies to develop e-commerce further, making it more accessible and personalized to meet individual needs. This study aims to explore the psychosocial factors (subjective norms; faith; consciousness; perceived control) that affect AI-enabled ease of use and their impact on purchase intention in online retail. We will also assess the mediating effect of AI-enabled ease of use between psychosocial factors and consumer purchase intention. A quantitative methodology was used, and 1438 responses were collected from Portuguese consumers on e-retail. Structural equation modeling was used for the statistical treatment. The findings indicate that subjective norms do not positively impact AI-enabled ease of use, whereas factors such as faith, consciousness, and perceived control do enhance it. Furthermore, AI-enabled ease of use itself boosts purchase intention. Additionally, the effects of subjective norms, faith, consciousness, and perceived control on purchase intention are significantly enhanced when mediated by AI-enabled ease of use, highlighting the crucial role of usability in shaping consumer purchase behavior. The contribution of this study has been made through the formulation model that provides a systematized perspective about the influencers of purchase intentions and extends the knowledge about the impact of artificial intelligence in e-retail. Furthermore, this study offers insights into the impact of artificial intelligence in e-commerce-artificial intelligence directly affects purchase intentions and plays an important mediator role in the interaction mechanisms between psychosocial factors and purchase intentions.

Fast Fourier-Chebyshev Approach to Real-Space Simulations of the Kubo Formula.

The Kubo formula is a cornerstone in our understanding of near-equilibrium transport phenomena. While conceptually elegant, the application of Kubo's linear-response theory to interesting problems is hindered by the need for algorithms that are accurate and scalable to large lattice sizes beyond one spatial dimension. Here, we propose a general framework to numerically study large systems, which combines the spectral accuracy of Chebyshev expansions with the efficiency of divide-and-conquer methods. We use the hybrid algorithm to calculate the two-terminal conductance and the bulk conductivity tensor of 2D lattice models with over 10^{7} sites. By efficiently sampling the microscopic information contained in billions of Chebyshev moments, the algorithm is able to accurately resolve the linear-response properties of complex systems in the presence of quenched disorder. Our results lay the groundwork for future studies of transport phenomena in previously inaccessible regimes.

Brugada Phenocopy Caused by Intracranial Hemorrhage.

Brugada syndrome (BrS) is a congenital channelopathy associated with an increased risk of malignant ventricular arrhythmias and sudden cardiac death in individuals without any structural cardiopathy. Brugada phenocopies (BrPs) are clinical entities that present electrocardiographic patterns similar to those of BrS that are elicited only under transitory pathophysiological conditions, with normalization of the ECG pattern after the resolution of those conditions. We present a rare case of BrP due to intracranial hemorrhage. We also present and discuss the diagnostic criteria for BrPs and their application to this case.

Gradenigo's Syndrome With Septic Lateral Sinus Thrombosis.

Gradenigo's syndrome (GS) is a rare but life-threatening complication of acute otitis media (AOM). It is classically defined as a clinical triad of acute otitis media, ipsilateral sixth (abducens) nerve palsy, and pain in the distribution of the first and second branches of the trigeminal nerve. Another rare but serious complication of AOM is venous sinus thrombosis, which is often associated with GS. The diagnosis of these conditions requires clinical suspicion, sound interpretation of signs and symptoms, and the use of the correct imaging techniques. Here, we present the case of an 81-year-old man with a previous history of recurrent otitis media, who presented with GS and septic lateral sinus thrombosis. The clinical presentation, physiopathology, and management of these conditions are discussed.

Diverging or converging to a green world? Impact of green growth measures on countries' economic performance.

Green growth has emerged in recent years to respond to environmental problems caused by climate change and the scarcity of resources. However, today's green growth involves environmental, social and financial dimensions. In this context, many countries are currently seeking green growth for their economic development through the efficient use of their resources. This study aims to assess the impact of green growth performance on the economic development of countries. A quantitative approach was applied to a sample of 172 countries worldwide, and the formulated hypotheses were tested through multiple linear regressions estimated by the ordinary least squares method. The economic development of countries was measured by the Human Development Index (HDI) and measures the sustainability performance of countries by the Green Growth Index (GGI). The results of this study demonstrate that (i) the measures of green growth performance have a positive impact on the economic development of high-income, upper-middle-income, and lower-middle-income economies, (ii) in poorer economies, less is the contribution of green growth to economic development, mainly because they neglecting the social dimension despite the numerous existing projects in these economies for greater inclusion and (iii) green economic opportunities (green investment, green trade, green employment and green innovation) do not influence green economic development in all analysed economies. Consequently, suggestions were made for policymakers from different groups of countries to increase and accelerate their sustainable green growth. Literature on economic development and green growth is still scarce, especially at the empirical level, and few studies use the 2020 GGI data. In addition, this study also uses recent rankings of world economies to categorize the economic development of countries.

Deep Learning-Based Energy Expenditure Estimation in Assisted and Non-Assisted Gait Using Inertial, EMG, and Heart Rate Wearable Sensors.

Energy expenditure is a key rehabilitation outcome and is starting to be used in robotics-based rehabilitation through human-in-the-loop control to tailor robot assistance towards reducing patients' energy effort. However, it is usually assessed by indirect calorimetry which entails a certain degree of invasiveness and provides delayed data, which is not suitable for controlling robotic devices. This work proposes a deep learning-based tool for steady-state energy expenditure estimation based on more ergonomic sensors than indirect calorimetry. The study innovates by estimating the energy expenditure in assisted and non-assisted conditions and in slow gait speeds similarly to impaired subjects. This work explores and benchmarks the long short-term memory (LSTM) and convolutional neural network (CNN) as deep learning regressors. As inputs, we fused inertial data, electromyography, and heart rate signals measured by on-body sensors from eight healthy volunteers walking with and without assistance from an ankle-foot exoskeleton at 0.22, 0.33, and 0.44 m/s. LSTM and CNN were compared against indirect calorimetry using a leave-one-subject-out cross-validation technique. Results showed the suitability of this tool, especially CNN, that demonstrated root-mean-squared errors of 0.36 W/kg and high correlation (ρ > 0.85) between target and estimation (R¯2 = 0.79). CNN was able to discriminate the energy expenditure between assisted and non-assisted gait, basal, and walking energy expenditure, throughout three slow gait speeds. CNN regressor driven by kinematic and physiological data was shown to be a more ergonomic technique for estimating the energy expenditure, contributing to the clinical assessment in slow and robotic-assisted gait and future research concerning human-in-the-loop control.

A multi-camera and multimodal dataset for posture and gait analysis.

Monitoring gait and posture while using assisting robotic devices is relevant to attain effective assistance and assess the user's progression throughout time. This work presents a multi-camera, multimodal, and detailed dataset involving 14 healthy participants walking with a wheeled robotic walker equipped with a pair of affordable cameras. Depth data were acquired at 30 fps and synchronized with inertial data from Xsens MTw Awinda sensors and kinematic data from the segments of the Xsens biomechanical model, acquired at 60 Hz. Participants walked with the robotic walker at 3 different gait speeds, across 3 different walking scenarios/paths at 3 different locations. In total, this dataset provides approximately 92 minutes of total recording time, which corresponds to nearly 166.000 samples of synchronized data. This dataset may contribute to the scientific research by allowing the development and evaluation of: (i) vision-based pose estimation algorithms, exploring classic or deep learning approaches; (ii) human detection and tracking algorithms; (iii) movement forecasting; and (iv) biomechanical analysis of gait/posture when using a rehabilitation device.

Comparison of Laccases and Hemeproteins Systems in Bioremediation of Organic Pollutants.

AIM: Laccases and peroxidases have attracted great interest for industrial and environmental applications. These enzymes have a broad substrate range and a robust oxidizing ability. Moreover, using mediators or co-oxidants makes it possible to increase their catalytic activity and extend their substrate scope to more resistant chemical structures. BACKGROUND: Fungal laccases and ligninolytic peroxidases, mainly lignin and manganese peroxidases, are the privileged oxidoreductases for bioremediation processes. Nonetheless, an increasing diversity of laccases and peroxidase-type enzymes has been proposed for environmental technologies. OBJECTIVE: This article aims to provide an overview of these enzymes and compare their applicability in the degradation of organic pollutants. METHODS: Fundamental properties of the proteins are covered and applications towards polycyclic aromatic hydrocarbons (PAHs) and pesticides are specially focused. RESULTS: Laccases are multicopper oxidases initially studied for applications in the pulp and paper industry but able to oxidize a variety of environmentally concerning compounds. Relying on O2, laccases do not require peroxides nor auxiliary agents, like Mn2+, although suitable redox mediators are needed to attack the more recalcitrant pollutants (e.g., PAHs). True and pseudo-peroxidases use a stronger oxidant (H2O2) and the redox chemistry at the heme site generates high potential species that allow the oxidation of dyes and some pesticides. CONCLUSION: Lately, research efforts have been directed to enzyme discovery, testing with micropollutants, and improving biocatalysts' stability by immobilization and protein engineering. Further understanding of the effects of natural media components and solvents on the enzymes might lead to competitive enzymatic treatments of highly toxic media.

KITE: high-performance accurate modelling of electronic structure and response functions of large molecules, disordered crystals and heterostructures.

We present KITE, a general purpose open-source tight-binding software for accurate real-space simulations of electronic structure and quantum transport properties of large-scale molecular and condensed systems with tens of billions of atomic orbitals (N ∼ 1010). KITE's core is written in C++, with a versatile Python-based interface, and is fully optimized for shared memory multi-node CPU architectures, thus scalable, efficient and fast. At the core of KITE is a seamless spectral expansion of lattice Green's functions, which enables large-scale calculations of generic target functions with uniform convergence and fine control over energy resolution. Several functionalities are demonstrated, ranging from simulations of local density of states and photo-emission spectroscopy of disordered materials to large-scale computations of optical conductivity tensors and real-space wave-packet propagation in the presence of magneto-static fields and spin-orbit coupling. On-the-fly calculations of real-space Green's functions are carried out with an efficient domain decomposition technique, allowing KITE to achieve nearly ideal linear scaling in its multi-threading performance. Crystalline defects and disorder, including vacancies, adsorbates and charged impurity centres, can be easily set up with KITE's intuitive interface, paving the way to user-friendly large-scale quantum simulations of equilibrium and non-equilibrium properties of molecules, disordered crystals and heterostructures subject to a variety of perturbations and external conditions.

Taming chaos to sample rare events: The effect of weak chaos.

Rare events in nonlinear dynamical systems are difficult to sample because of the sensitivity to perturbations of initial conditions and of complex landscapes in phase space. Here, we discuss strategies to control these difficulties and succeed in obtaining an efficient sampling within a Metropolis-Hastings Monte Carlo framework. After reviewing previous successes in the case of strongly chaotic systems, we discuss the case of weakly chaotic systems. We show how different types of nonhyperbolicities limit the efficiency of previously designed sampling methods, and we discuss strategies on how to account for them. We focus on paradigmatic low-dimensional chaotic systems such as the logistic map, the Pomeau-Maneville map, and area-preserving maps with mixed phase space.

Effect of anesthetic, tag size, and surgeon experience on postsurgical recovering after implantation of electronic tags in a neotropical fish: Prochilodus lineatus (Valenciennes, 1837) (Characiformes: Prochilodontidae)

Implantation of telemetry transmitters in fish can be affected by different parameters. This study aimed to evaluate the effect of type of anesthetic, tag size, and surgeon experience on surgical and postsurgical wound healing in the neotropical fish Prochilodus lineatus . In total, eighty fish were surgically implanted with telemetry transmitters and forty fish were kept as controls. Forty fish were implanted with a small tag and other forty were implanted with a large tag. Similarly, forty fish were anesthetized with eugenol and forty fish were anesthetized by electroanesthesia, and forty surgeries were performed by an expert surgeon and forty surgeries were performed by novice surgeons. At the end of the experimental period seventeen (21.3%) tagged fish had postsurgical complications, including death (1.3%), tag expulsion (2.5%), antenna migration (2.5%), and infection (15%). Tag size was the key determinant for postsurgical complications. Surgical details and postsurgical wound healing were not affected by type of anesthetic. Incision size, duration of surgery, and wound area were significantly affected by tag size and surgeon experience, and the number of sutures was significantly affected by tag size only. The results indicate that successful implantation of telemetry transmitters is dependent upon surgeon experience and tag size.(AU)

A implantação de transmissores em peixes pode ser afetada por diversos aspectos. Este estudo objetivou avaliar a influência do tamanho do transmissor, do tipo de anestésico e da experiência do cirurgião em parâmetros cirúrgicos e recuperação pós-cirúrgica do peixe neotropical Prochilodus lineatus . Foram marcados oitenta indivíduos com transmissores de telemetria, enquanto outros quarenta foram utilizados como controle. Quarenta indivíduos foram marcados com um transmissor pequeno e outros quarenta com um transmissor maior. Foram utilizados dois tipos de anestésico sendo quarenta indivíduos anestesiados por eletronarcose e outros 40 por eugenol e as cirurgias foram realizadas por dois grupos de cirurgiões, experientes e inexperientes com quarenta peixes em cada grupo. Dezessete peixes (21,3%) apresentaram impactos diretos resultantes da cirurgia como o óbito (1,3%), perda do transmissor (2,5%), migração da antena (2,5%) e infecções internas (15%). Estes efeitos estão ligados ao tamanho do transmissor utilizado. A experiência do cirurgião possui relação direta em três parâmetros cirúrgicos (tamanho da incisão, tempo de cirurgia e área de cicatrização). O tamanho dos transmissores utilizados possui relação com quatro parâmetros (tamanho da incisão cirúrgica, número de suturas utilizadas, tempo de cirurgia e área de cicatrização). O anestésico não teve relação com os parâmetros cirúrgicos. Os resultados indicam que tanto a dimensão dos transmissores quanto a experiência dos cirurgiões têm impacto direto no sucesso de implantação dos transmissores.(AU)

Induced spawning and early ontogeny in hatchery-reared catfish Zungaro jahu (Siluriformes: Pimelodidae)

Hatchery-kept catfish jahus Zungaro jahu (Ihering, 1898) were induced to spawn with carp pituitary extract. The telolecithal eggs were round (1.6 ± 0.1 mm in diameter), demersal, free, and covered with a 0.4 mm-thick jelly coat. The gonadosomatic index of 2.8 was comparable to that of other Pimelodidae. The number of eggs x g of ova-1 was 804 ± 144. Hatching occurred 14.5 h after fertilization, at a temperature of 27.3 ± 0.4º C. The newly-hatched embryos measured 3.9-4.3 mm of total length (TL). At 18 h post-hatching (HPH; 5.3 ± 0.1 mm TL), the retina was pigmented, the mouth opened and dorsoflexion of the notochord had initiated. At 36 HPH (6.4 ± 0.2 mm TL), fusiform chromatophores were vertically arranged in the primordial fin fold and the notochord was dorsoflexed. The yolk sac was almost exhausted by 48 HPH (7.3 ± 0.2 mm TL). At 128 HPH (8.6 ± 0.6 mm TL) the pectoral, dorsal, adipose, caudal, anal, and pelvic fins were readily observable whereas the primordial fin fold was no longer visible. At 224 HPH (16.6 ± 2.5 mm TL), the metamorphosis was completed and the larvae had acquired the juvenile appearance.

Jaús Zungaro jahu (Ihering, 1898), mantidos em estação de piscicultura, foram induzidos à reprodução com extrato bruto de hipófise de carpa. Seus ovos são telolécitos, arredondados (1,6 ± 0,1 mm de diâmetro), demersais, livres e cobertos por uma capa gelatinosa com 0,4 mm de espessura. O índice gonadossomático (peso da ova : peso total do peixe) de 2,8 foi semelhante ao de outros Pimelodidae. O número de ovos x g de ova-1 foi 804 ± 144. A eclosão dos embriões ocorreu 14,5 h pós-fertilização à temperatura de 27,3 ± 0,4º C. Os embriões recém-eclodidos apresentaram 3,9-4,3 mm de comprimento total (CT). Dezoito horas pós-eclosão (HPE) e 5,3 ± 0,1 mm CT, a retina estava pigmentada, a boca aberta e a flexão da notocorda tinha se iniciado. Às 36 HPE (6,4 ± 0,2 mm CT), observaram-se cromatóforos fusiformes alinhados verticalmente na nadadeira primordial; a notocorda já se encontrava flexionada. O saco vitelínico encontrava-se quase que inteiramente absorvido às 48 HPE (7,3 ± 0,2 mm CT). Com 128 HPE (8,6 ± 0,6 mm TL), as nadadeiras peitoral, dorsal, adiposa, caudal, anal e pélvica estavam formadas e a nadadeira primordial já havia sido reabsorvida. Com 224 HPE (16,6 ± 2,5 mm CT), a metamorfose se completou e as larvas se transformaram em juvenis.