Miracle-dz/UniFAR-FTUs huggingface dataset:
Tradeoff in the supply and demand for CO2 dominates the divergence of net photosynthesis rates of functional plants in alpine ecosystems

The responses of photosynthesis to change of temperature and CO2 concentration are divergent among various alpine plant species at high altitude regions; however, very few direct in situ measurements have been conducted to compare photosynthetic capacity among different functional plants along altitude gradients in the Qinghai‐Tibet Plateau (QTP). This study measured the net photosynthetic assimilation rate (An), maximum carboxylation rate (Vcmax), maximum electron transport rate (Jmax), stomatal conductance (gs) and mesophyll conductance (gm) for CO2 of three plant functional types (PFTs, sedge, grass and shrub) and functional traits at different altitudes in the Qinghai Lake watershed during growing season. Meanwhile we simulated An of the PFTs under potential future scenario. Results indicate that grass maintain a relatively stable An by decreasing Vcmax, Jmax, ratio of Jmax to Vcmax (J/V) and gs, while slightly increasing gm with increasing altitudes. In contrast, the An of sedge and shrubs increased with rising Vcmax, Jmax, gs and gm values, resulting in a large increment in the An at low altitudes. Grass was less sensitive to temperature by reducing the supply of CO2, while sedge and shrub increased. Ca was a more dominant factor than Ta in affecting the An of grass. The order of rising An in PFTs was shrub > sedge > grass, and the An of alpine meadow was found to increase more under the Representative Concentration Pathways (RCP) 4.5 and 8.5 scenarios. Our results indicate that grass may be more resistant to future warming and suggested that considering PFTs is of great significance for improving the simulating of the response of vegetation physiological and ecological processes to future climate change in alpine regions.
A model for charge transfer in buried-channel charge-coupled devices at low temperature

Charge transfer in buried-channel charge-coupled devices (CCDs) is explored with a one-dimensional numerical model which describes the capture and emission of electrons from a shallow donor level in silicon through the use of the Shockley-Read-Hall generation-recombination theory. Incorporated in the model are the three-dimensional Poole-Frenkel barrier lowering theory of A. K. Jonscher (1967) and J. L. Hartke (1968) and the low-temperature form of Poisson's equation. Reasonable agreement of the model with experimental data taken from the buried-channel CCDs of a PtSi Schottky barrier infrared image sensor is found. Moreover, the value for the capture cross section of electrons to the shallow phosphorus level in silicon inferred from the model follows the cascade theory for capture by M. Lax (1959) and agrees roughly with determinations made by other experimenters. >
Study on Prevalence of Hard Ticks and Their Associated Risk Factors in Small Ruminants of Boloso Sore Districts of Wolaita Zone, Southern Ethiopia

Background Ticks and tick-borne infections are the most serious health threats to small ruminants in Ethiopia, resulting in huge economic losses. Methods A cross-sectional study using a simple random sampling technique was conducted to determine the prevalence and potential risk factors of hard ticks in small ruminants of the Boloso Sore district of Wolaita Zone. Ticks were identified to species level under a stereomicroscope using morphological identification keys. Results From a total of 400 examined animals, 68.75% (275/400) of them were infested with hard ticks with the respective prevalence of 69.09% (152/220) in goats and 68.33% (123/180) in sheep. A total of 1192 (552 males and 640 females) adult ixodid ticks that belong to a total of four species, which were grouped under three genera: Amblyomma, Hyalomma, and Rhipicephalus, and one subgenus; Boophilus were collected from the head, ear, under tail and legs of goats and sheep. In this study, Amblyomma variegatum 44.97% (536/1192) was found to be the most abundant tick species followed by Boophilus decoloratus 30.79% (367/1192), Rhipicephalus pulchellus 20.47% (244/1192), and Hyalomma truncatum 3.77% (45/1192). The sex, age, and body condition score of animals with a high prevalence of hard ticks showed statistically significant differences (p<0.05). Male ticks dominated females in all cases except for Boophilus decoloratus. There was no statistically significant relationship (p > 0.05) between tick infestation and animal origin or species. Conclusion Ticks were the most significant production and health constraints for small ruminants in the study region. Therefore, the increasing threat of ticks of small ruminants warrants urgent strategic application of acaricides and the creation of awareness among livestock owners to prevent and control tick infestation.
Reusing Delivery Drones for Urban Crowdsensing

Thanks to the increasing number and massive coverage, delivery drones, equipped with various sensors, have demonstrated significant but unexplored potentials for large-scale and low-cost urban sensing during package delivery. In this paper, we propose novel studies on the reutilization of such delivery drone resources to fill this void in urban crowdsensing. Accounting for interdependency between flying/sensing and drone delivery weight, we jointly optimize route selection, sensing time, and delivery weight allocation, to maximize delivery and sensing utility under drones’ energy constraints. This problem is formulated as a non-convex mixed-integer non-Linear programming problem, which is proved to be NP-hard. To address this intricate problem, we propose near-optimal algorithms that leverage the equivalent objective function construction, the local search scheme, and the alternating iteration technique. Theoretical analysis indicates that our algorithms can achieve <inline-formula><tex-math notation="LaTeX">$\frac{1}{4+\varepsilon }$</tex-math><alternatives><mml:math><mml:mfrac><mml:mn>1</mml:mn><mml:mrow><mml:mn>4</mml:mn><mml:mo>+</mml:mo><mml:mi>ɛ</mml:mi></mml:mrow></mml:mfrac></mml:math><inline-graphic xlink:href="xiang-ieq1-3127212.gif"/></alternatives></inline-formula>-approximation ratio (where <inline-formula><tex-math notation="LaTeX">$\varepsilon$</tex-math><alternatives><mml:math><mml:mi>ɛ</mml:mi></mml:math><inline-graphic xlink:href="xiang-ieq2-3127212.gif"/></alternatives></inline-formula> is an arbitrarily small positive parameter) and the convergence guarantee in polynomial time, for the scenarios of fixed and adjustable delivery weights, respectively. Extensive trace-based simulations, field experiments, and the real-world application demonstrate that ours can significantly improve the delivery & sensing utility by <inline-formula><tex-math notation="LaTeX">$124.7\%$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>124</mml:mn><mml:mo>. </mml:mo><mml:mn>7</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="xiang-ieq3-3127212.gif"/></alternatives></inline-formula> and the energy utilization rate by <inline-formula><tex-math notation="LaTeX">$72.2\%$</tex-math><alternatives><mml:math><mml:mrow><mml:mn>72</mml:mn><mml:mo>. </mml:mo><mml:mn>2</mml:mn><mml:mo>%</mml:mo></mml:mrow></mml:math><inline-graphic xlink:href="xiang-ieq4-3127212.gif"/></alternatives></inline-formula> on average, compared with the drone delivery without reusing.
Ecosystem services and disservices associated with pastoral systems from Patagonia, Argentina – A review

Pastoral systems worldwide secure rural livelihoods in the harshest environments on Earth. Their low productivity per area unit or head makes them the subject of much criticism with regard to their environmental impact, particularly in relation to global warming, desertification and land degradation. Such is the case of the traditional pastoral systems of Patagonia, a vast and isolated region where sedentary and mobile pastoralism coexist and contribute to shape landscapes and cultures. We argue that pastoral systems provide a wide range of ecosystem services that may compensate for their negative impact on the environment. We review the scarcely available evidence from Patagonia to identify ecosystem services and disservices associated with pastoralism, and pay special attention to the carbon balance: with C footprints between 10 to 40 kg CO2-eq.kg−1 carcass, pastoral systems in dry Patagonia are below or within the range of semi-extensive livestock systems worldwide (35–45 CO2-eq. kg−1 carcass). To inform development and policy, the assessment of trade-offs and synergies between ecosystem services needs to incorporate the intertwined social and ecological dynamics of complex pastoral systems, along resource regenerative trajectories.
User experience evaluation of low cost EEG headsets

İnsan bilgisayar etkileşiminde gelecek vadeden önemli alanlardan biri olan beyin bilgisayar ara yüzlerinde EEG başlıkları oldukça yaygın olarak kullanılmaktadır. Bu çalışmada, düşük maliyetli iki farklı EEG başlığı olan NeuroSky MindWave ve Emotiv EPOC’un dikkat ve rahatlama gerektiren görevlerde performans karşılaştırması, kullanıcı deneyimi ve kullanılabilirlik değerlendirmesi yapılmaktadır. Çalışmada 12 gönüllü katılımcıdan yüksek bilişsel yük gerektiren dikkat görevi ve rahatlama görevi gerçekleştirmeleri istenmiştir. Kullanıcı deneyimini değerlendirmek için Affect Grid ölçeği ve AttrakDiff anketi kullanılırken cihazlara ait kullanılabilirlik problemlerini ortaya koyabilmek için NASA Zihinsel İş Yükü anketi ve Sistem Kullanılabilirlik Ölçeği kullanılmıştır. İstatistiksel sonuçlar incelendiğinde rahatlama görevlerinde NeuroSky MindWave EEG başlığının Emotiv EPOC EEG başlığına oranla daha başarılı olduğu gözlemlenmiştir. Dikkat gerektiren görevlerde ise her ikisi de benzer doğrultuda sonuçlar vermiştir. Kullanıcı deneyimi değerlendirmesine bakıldığında, katılımcıların her iki EEG başlığı kullanım esnasında yorgunluk hissettikleri ancak buna rağmen cihazları kullanımından memnun oldukları gözlemlenmiştir. Kullanılabilirlik açısından bakıldığında ise NeuroSky MindWave için daha olumlu görüşler bildirmişlerdir. One of the promising areas in human computer interaction is the brain computer interfaces and EEG headsets are widely used technology in this domain. In this study, performance comparison of two different lowcost EEG headsets, NeuroSky MindWave and Emotiv EPOC EEG, in tasks requiring attention and relaxation, and their user experience and usability evaluations were conducted. There were 12 participants who were asked to perform attention tasks that require high cognitive load and relaxation tasks. While the Affect Grid scale and AttrakDiff questionnaire were used to evaluate the user experience, the NASA Task Load Index and System Usability Scale were used to reveal the usability problems of the devices. When the statistical results were examined, it was observed that the NeuroSky MindWave was more successful than the Emotiv EPOC in relaxation tasks. However, both have similar results in tasks requiring attention. According to the user experience evaluation results, it was observed that the participants felt tired while using both EEG heads, but were still satisfied with the use of the devices. They reported more positive opinions for NeuroSky MindWave in terms of usability.
Adaptive Aiding of Human-Robot Teaming

In many emerging civilian and military operations, human operators are increasingly being tasked to supervise multiple robotic uninhabited vehicles (UVs) with the support of automation. As 100% automation reliability cannot be assured, it is important to understand the effects of automation imperfection on performance. In addition, adaptive aiding may help counter any adverse effects of static (fixed) automation. Using a high-fidelity multi-UV simulation involving both air and ground vehicles, two experiments examined the effects of automation reliability and adaptive automation on human-system performance with different levels of task load. In Experiment 1, participants performed a reconnaissance mission while assisted with an automatic target recognition (ATR) system whose reliability was low, medium, or high. Overall human-robot team performance was higher than with either human or ATR performance alone. In Experiment 2, participants performed a similar reconnaissance mission with no ATR, static automation, or with adaptive automation keyed to task load. Participant trust and self-confidence were higher and workload was lower for adaptive automation compared with the other conditions. The results show that human-robot teams can benefit from imperfect static automation even in high task load conditions and that adaptive automation can provide additional benefits in trust and workload.
Timely Diagnosis of Acute Lymphoblastic Leukemia Using Artificial Intelligence-Oriented Deep Learning Methods

Background Leukemia is fatal cancer in both children and adults and is divided into acute and chronic. Acute lymphoblastic leukemia (ALL) is a subtype of this cancer. Early diagnosis of this disease can have a significant impact on the treatment of this disease. Computational intelligence-oriented techniques can be used to help physicians identify and classify ALL rapidly. Materials and Method. In this study, the utilized dataset was collected from a CodaLab competition to classify leukemic cells from normal cells in microscopic images. Two famous deep learning networks, including residual neural network (ResNet-50) and VGG-16 were employed. These two networks are already trained by our assigned parameters, meaning we did not use the stored weights; we adjusted the weights and learning parameters too. Also, a convolutional network with ten convolutional layers and 2∗2 max-pooling layers—with strides 2—was proposed, and six common machine learning techniques were developed to classify acute lymphoblastic leukemia into two classes. Results The validation accuracies (the mean accuracy of training and test networks for 100 training cycles) of the ResNet-50, VGG-16, and the proposed convolutional network were found to be 81.63%, 84.62%, and 82.10%, respectively. Among applied machine learning methods, the lowest obtained accuracy was related to multilayer perceptron (27.33%) and highest for random forest (81.72%). Conclusion This study showed that the proposed convolutional neural network has optimal accuracy in the diagnosis of ALL. By comparing various convolutional neural networks and machine learning methods in diagnosing this disease, the convolutional neural network achieved good performance and optimal execution time without latency. This proposed network is less complex than the two pretrained networks and can be employed by pathologists and physicians in clinical systems for leukemia diagnosis.
PREPARATION AND STABILITY EVALUATION OF LL-37 CREAM

Objective: The present study aimed to prepare LL-37 in a cream formulation (O/W emulsion) and evaluate its stability by determining the physical changes in the cream and concentration of LL-37 using validated high-performance liquid chromatography. Methods: The method was conducted at room temperature using a C18 column (5 µm × 250 mm × 4.6 mm) as a stationary phase, a mixture of 0.1% trifluoroacetic acid (TFA)/water (A) and 0.1% TFA/acetonitrile (B) (85:15) as the mobile phase, a flow rate of 1.0 mL/min, and photodiode array set at 228 nm as the detector. The method was validated in compliance with the Association of Official Analytical Chemists and International Conference on Harmonization guidelines. It demonstrated excellent linearity, accuracy, precision, specificity, the limit of detection, and limit of quantitation. Results: The chromatographic analysis indicated minimal degradation of LL-37 during the 12-week, with a predicted expiry time of 99 and 75 mo stored at 4 °C and 28 °C, respectively. Conclusion: LL-37 cream establishes good physical characteristics and stabilizes the active ingredient, especially at 4 °C and 28 °C storage. Therefore, the emulsion delivery system of LL-37 cream is harmless and stable as a novel alternative vehicle of LL-37.
Remoção de matéria orgânica, de nutrientes e de coliformes no processo anaeróbio em dois estágios (reator compartimentado seguido de reator UASB) para o tratamento de águas residuárias de suinocultura

Neste trabalho, avaliou-se o efeito das aguas residuarias de suinocultura, com concentracoes medias de solidos suspensos totais variando de 4.591 a 13.001 mg L-1, no desempenho de processo anaerobio, em dois estagios, compostos por reator compartimentado (ABR) e reator de fluxo ascendente com manta de lodo (UASB), instalados em serie, em escala- -piloto (volumes de 530 e 120 L, respectivamente), submetidos a tempos de detencao hidraulica (TDH) de 60; 36 e 24 h no primeiro reator, e de 13,6; 8,2 e 5,4 h no segundo reator. As eficiencias medias de remocao de DQOtotal variaram de 69 a 84% no reator ABR e de 39 a 58% no reator UASB, resultando em valores medios de 87 a 94% para o sistema de tratamento anaerobio em dois estagios, com carga orgânica volumetrica (COV) na faixa de 11,5 a 18,0 g DQOtotal (L d)-1 no reator ABR, e de 4,2 a 13,4 g DQOtotal (L d)-1 no reator UASB. A producao volumetrica maxima de metano de 0,227 m3 CH4 (m3 reator d)-1 ocorreu no reator UASB, com COV de 10,6 g DQOtotal (L d)-1 e TDH de 5,4 h. As maiores eficiencias de remocao de coliformes totais e termotolerantes (99,7%), DQOdiss (94%), SST (96%), NTK (71%), P-total (61%) e outros nutrientes, no sistema de tratamento anaerobio em dois estagios, foram obtidas com o TDH de 73,6 h e temperatura climatologica media de 24,6 °C, aplicando-se a menor COV (de 11,5 g DQOtotal (L d)-1 no reator ABR, e de 4,2 g DQOtotal (L d)-1 no reator UASB) com a maior concentracao de SST do afluente (13.001 mg L-1).
Effect of Ingredients on the Bacteriological Profile of Ready to Eat Meat Sandwiches

| The current study aimed to investigate the bacteriological quality of the ready-to-eat (RTE) meat sandwiches prepared using the meat and treated ingredients viz., green salad and tahini sauce. Two hundred and forty samples of RTE meat sandwiches, vegetable salad, and tahini sauce were used in the study. The washing of vegetable salad for 10 min with water providing 50 ppm chlorine reduced (p < 0.05) the aerobic plate count (APC), Bacillus cereus (B. cereus) and Staphylococcus aureus (S. aureus) count. Similarly, addition of 1% garlic essential oil during formulation of tahini sauce reduced (p < 0.05) APC, B. cereus and S. aureus count. The counts in RTE meat sandwiches after using treated green salad and tahini sauce reduced (p < 0.05) APC count from (5.58 ± 1.21 and 6.54 ± 1.12) to (3.2 ± 0.22 and 4. 89 ± 0.31) log10CFU/g. The counts of B.cereus reduced (p < 0.05) from (2.98 ± 0.11 and 3.34 ± 0.15) to (<2 and 2. 49 ± 0.09) and S.aureus reduced (p < 0.05) from (3.18 ± 0.15 and 3.85 ± 0.13) to (<2 and 2. 87± 0.09) log10CFU/g. These results demonstrated that use of treated vegetable salad (washed by chlorine water) and tahini sauce (containing 1% garlic essential oil) in preparation of RTE meat sandwiches results the improved bacteriological quality of RTE meat sandwiches.
An Experimental Powered Lower Limb Prosthesis Using Proportional Myoelectric Control

One way to provide powered lower limb prostheses with greater adaptability to a wearer's intent is to use a neural signal to provide feedforward control of prosthesis mechanics. We designed and tested the feasibility of an experimental powered ankle-foot prosthesis that uses pneumatic artificial muscles and proportional myoelectric control to vary ankle mechanics during walking. The force output of the artificial plantar flexor muscles was directly proportional to the subject's residual gastrocnemius muscle activity. The maximum force generated by a pair of artificial muscles fixed at nominal length was 3513 N. The maximum planter flexion torque that could be generated during walking was 176 Nm. The force bandwidth of the pneumatic artificial muscles was 2 Hz. The electromechanical delay was 33 ms, the time to peak tension was 48 ms, and the half relaxation time was 50 ms. We used two artificial muscles as dorsiflexors and two artificial muscles as plantar flexors. The prosthetic ankle had 25 deg of dorsiflexion and 35 deg of plantar flexion with the artificial muscles uninflated. The intent of the device was not to create a commercially viable prosthesis but to have a laboratory prototype to test principles of locomotor adaptation and biomechanics. We recruited one unilateral transtibial amputee to walk on a treadmill at 1.0 m/s while wearing the powered prosthesis. We recorded muscle activity within the subject's prescribed prosthetic socket using surface electrodes. The controller was active throughout the entire gait cycle and did not rely on detection of gait phases. The amputee subject quickly adapted to the powered prosthesis and walked with a functional gait. The subject generated peak ankle power at push off that was similar between amputated and prosthetic sides. Our results suggest that amputees can use their residual muscles for proportional myoelectric control to alter prosthetic mechanics during walking.
Resonant learning in scale-free networks

Over the last decades, analyses of the connectivity of large biological and artificial networks have identified a common scale-free topology, where few of the network elements, called hubs, control many other network elements. In monitoring the dynamics of networks’ hubs, recent experiments have revealed that they can show behaviors oscillating between ‘on’ and ‘off’ states of activation. Prompted by these observations, we ask whether the existence of oscillatory hubs states could contribute to the emergence of specific network dynamical behaviors. Here, we use Boolean threshold networks with scale-free architecture as representative models to demonstrate how periodic activation of the network hub can provide a network-level advantage in learning specific new dynamical behaviors. First, we find that hub oscillations with distinct periods can induce robust and distinct attractors whose lengths depend upon the hub oscillation period. Second, we determine that a given network can exhibit series of different attractors when we sequentially change the period of hub pulses. Using rounds of evolution and selection, these different attractors could independently learn distinct target functions. We term this network-based learning strategy resonant learning, as the emergence of new learned dynamical behaviors depends on the choice of the period of the hub oscillations. Finally, we find that resonant learning leads to convergence towards target behaviors over an order of magnitude faster than standard learning procedures. While it is already known that modular network architecture contributes to learning separate tasks, our results reveal an alternative design principle based on forced oscillations of the network hub. SIGNIFICANCE Large networks of interconnected components such as genes or machines can coordinate complex behavioral dyamics. One outstanding question has been to identify the design principles that allow networks to learn new behaviors. Here, in simulating learning cycles, we randomly modify the interactions between components and select networks that exhibit a desired behavior. Surprisingly, we find that networks can learn new behaviors faster when the state of the most connected network component is forced to oscillate during learning. Remarkably, using distinct periods of oscillations allows a given network to learn distinct behaviors. While it is known that modular network architecture contributes to learning separate tasks, our results reveal an alternative design principle for which modules are not needed.