Miracle-dz/UniFAR-FTUs huggingface dataset:
Emotional Regulation and Affects in Patients With Borderline Personality Disorder

Background: The regulation of emotions and affective strategies have been shown to be relevant in the clinic of borderline personality disorder (BPD), however, the studies carried out are still not conclusive on the influencing role of these two variables on the course of the TLP. The need for empirical evidence on the relationship between the internal components of these manifestations is faced: cognitive reappraisal, expressive suppression, positive affect and negative affect. Result: The results indicate that the psychological variables studied present more dysfunctional values ​​in patients with BPD. The symptomatic of BPD does not moderate the relationship between cognitive reappraisal and negative affect; and cognitive reappraisal together with positive affect are associated with fewer BPD symptoms. Conclusion: The results obtained offer different clinical implications in the affective and emotional context of BPD, however, it would be necessary to use alternative measures of the emotional pattern, such as physiological methodologies to have more defining results.
Research on Empirical Evidence for Individualization of Gender Roles across Generations in China

This study aims to understand the trends in perceptions, preferences, and choices of gender roles among Chinese women born in different generations during the process of modernization and westernization. Individualization theory predicts that as industrialization progresses, traditional moral and social responsibilities shift from social values and family obligations to individual judgments and decisions. We predict that in modern China, while gender equality and feminist consciousness are more prominent, women are more explicitly supportive of gender rights and equality in terms of stereotypical expectations and family role assignments. However, we also predict that implicit perceptions and stereotypes still exist in the form of individual choices and social judgments. In a study comparing the attitudes of men (N=210) and women (N=249) born over a fifty-year period (from 60' to 00') toward marital responsibilities and personal choices of daily activities, we found that, consistent with our predictions, younger women showed significantly higher explicit support and preference for daily activities that violate traditional gender stereotypes compared to men. However, their judgments of women who openly violate gender expectations in their marriages did not increase, and their personal choices of daily activities were consistent with gender stereotypical role assignments.
Sargassum Influx on the Mexican Coast: A Source for Synthesizing Silver Nanoparticles with Catalytic and Antibacterial Properties

This work reports, for the first time, the synthesis of silver nanoparticles using extracts of the species of Sargassum natans and Sargassum fluitans (AgNPs-S). Their antibacterial and catalytic properties are compared with silver nanoparticles obtained by chemical synthesis (AgNPs-C). The characterization of AgNPs-S and AgNPs-C was carried out using ultraviolet–visible spectroscopy (UV–Vis), dynamic light scattering (DLS), zeta potential, a scanning electron microscope (SEM), X-ray diffraction (XRD), Fourier transform infrared spectroscopy (FTIR), and thermogravimetric analysis. The synthesis of silver nanoparticles using Sargassum extract was optimized through varying experimental parameters, such as the type of solvent used to prepare the extract, the volume of the extract, and the pH of the system. The most efficient sample (AgNPs-S) was prepared with a water–ethanol-based extract, using a 3:1 volumetric ratio of extract: a precursor salt with the addition of 1 mL of NaOH pH = 14. The AgNPs-C were spherical in shape, with an average particle size of 11.55 nm, while the AgNPs-S were polyhedral shaped, with an average particle size of 26.39 nm. The synthesized AgNPs-S were found to have significantly higher catalytic activity for the degradation of methylene blue and more effective antibacterial activity against Staphylococcus aureus and Pseudomonas aeruginosa than AgNPs-C.
Immediate Effects of Neural Slider and Neural Tensioner on Forward
 Bending in Subjects with Hamstring Tightness

Hamstring is a muscle group that has a tendency to develop tightness, which affects all age groups. The hamstring muscle affects pelvic motion because it originates from the sciatic surface of the pelvis. Hamstring flexibility is a critical parameter because a decreased extensibility of this muscle is a factor that predicts injuries, nonspecific back pain, and changes in the lumbopelvic rhythm. Maintaining hamstring flexibility is crucial for restoring musculoskeletal functions, such as the lumbopelvic rhythm. Carregaro and Coury et al. evaluated decreased hamstring flexibility for the lumbar and pelvic movements during a box lowering task and found that subjects with reduced flexibility showed more lumbar movements and limited pelvic movements during a box lowering task. Decreased hamstring flexibility limits hip movement while forward bending of the trunk and simultaneously results in excessive lumbar movement. The peripheral muscles and ligaments behind the lumbar spine are subjected to excessive tension and, consequently, cause low back pain. The effect of stretching exercises on hamstring flexibility during forward bending is an interesting subject for researchers. Some previous studies have investigated the effects of hamstring stretching on the lumbopelvic rhythm. Hasebe and colleagues performed a finger–floor distance to Immediate Effects of Neural Slider and Neural Tensioner on Forward Bending in Subjects with Hamstring Tightness
Smart Mobility Adoption: A Review of the Literature

Traffic congestion and air pollution continue to be serious concerns, especially in large cities, and going forward, this is not sustainable. Urban transport around the world is facing challenges, such as air pollution and inefficient use of resources, that often inhibit economic development. Simply building more roads cannot address such challenges. There is a need to integrate the urban infrastructure through smart connectivity. Smart mobility, as a vital cornerstone of a smart city, will potentially reduce traffic jams, commuting times, and road crashes and create an opportunity for passengers to customize their journeys. In fact, planning smart mobility solutions is among the top challenges for large cities around the world. It involves a set of deliberate actions backed by sophisticated technologies. The different elements and dimensions that characterize smart mobility are investigated to depict the overall picture surrounding the smart mobility domain. Additionally, the trends, opportunities, and threats inherent to smart mobility are addressed. There are four segments of smart mobility that are highlighted in this paper: intelligent transport systems, open data, big data analytics, and citizen engagement. These segments are all inter-related and play a crucial role in the successful implementation of smart mobility.
Exploring Omni-Channels for Customer-Centric e-Tailing

In this volatile post-COVID environment where customers look for ways to order products online using personal computers and mobile devices, a traditional sale/delivery of products via single distribution channel needs to be reassessed. As a revolutionary alternative to a conventional distribution channel, this paper proposes an omni-channel strategy. The omni-channel aims to maximize the customer shopping experience by diversifying and integrating the product purchase and delivery media through customer engagement. The omni-channel also facilitates the sales of products by allowing customers to seamlessly interact with retailers across the multiple channels such as websites, social media, brick-and-mortar stores, kiosks, call centers, and the like. Since the transformation of product sale, purchase, and delivery processes requires a new business mindset and innovative strategic initiatives, this paper sheds light on potential challenges and opportunities of implementing the omni-channel strategy, while identifying key success factors for the application of the omni-channel concept to e-tailing.
Achieving Testing Effects in an Authentic College Classroom

Background: Findings from the testing effect literature suggest several ways to achieve testing effects in an authentic classroom, but few consider instructor workload, equity, and resources that determine feasibility and sustainability of testing effect methods in practice. Objective: To determine elements and procedures from the testing effect literature for practical application, devise a method for feasibly and sustainably implementing testing effect methods in practice, and determine if a simple way to incorporate retrieval practice into an existing introduction to psychology course was sufficient to observe testing effects. Method: Quiz scores of Introductory Psychology sections with and without retrieval practice were compared. Sections with retrieval practice also compared the effects of repeated and new questions on quiz performance. Results: Students with retrieval practice performed significantly better on quizzes than those without. Repeated and new retrieval practice were equally superior. Conclusion: Retrieval practices can successfully be implemented, feasibly and sustainably, in an authentic classroom environment. Retrieval practice questions can be related to delayed practice questions, rather than exact repeats, to achieve a testing effect. Teaching Implications: Distributing low stakes multiple-choice questions throughout lectures is effective for increasing test performance. The current method was neither burdensome to workload, content, or resources.
Influence of energy supplementation on associative effects in Nellore bulls on a tropical pasture during the rainy season

The objective of this study was to evaluate the influence of energy supplementation on associative effects between forage and concentrate supplements and on the performance of beef cattle on a tropical pasture during the rainy season. Twenty-eight Nellore bulls averaging 19 months of age and 325.2 ± 4.1 kg were allotted to a completely randomized design and distributed into four paddocks of two hectares each with a tropical pasture for 84 d. The treatments consisted of bulls on Urochloa brizantha cv. Xaraés pasture without concentrate supplementation or bulls on Urochloa brizantha cv. Xaraés pasture receiving concentrate supplementation at 15 (S15), 30 (S30) or 45% (S45) of the total digestible nutrients (TDN) requirement All bulls had ad libitum access to mineral supplementation. The amount and chemical composition of the supplement were adjusted every 28 d. Forage and supplement intakes were evaluated in all animals using fecal markers. Crude protein: digestible organic matter ratio decreased with supplementation; consequently, the imbalance between dietary protein and energy increased. Forage intake decreased with increasing supplementation. The substitution rates of pasture for supplementary feed were 0.14, 0.33, and 0.46 for bulls from S15, S30, and S45 treatments, respectively. However, the apparent DM digestibility increased linearly with supplementation level. Supplementation improved the assimilation of ammonia-N in the rumen. Energy supplementation for Nellore bulls on tropical pastures during the rainy season provides excess energy relative to protein, resulting in a substitution effect of supplement intake on forage intake. Moreover, energy supplementation does not improve body weight gain. Protein sources should be added to supplements for balancing protein and energy levels, thereby reducing a likely substitution effect.
Physicochemical Characterisation and the Prospects of Biofuel Production from Rubberwood Sawdust and Sewage Sludge

This study aims to evaluate the physicochemical properties of rubberwood sawdust (RWS) and sewage sludge (SS) for producing biofuel or liquid products via pyrolysis and co-pyrolysis. The chemical and thermal properties of both samples were observed to have superior bioenergy production capabilities. RWS and SS had significantly different physicochemical properties, such as particle-size distribution, bulk density, ultimate and proximate analysis, lignocellulose composition, thermal-degradation behaviour, and major and minor elements. The composition of extractives was found to only marginally affect the end product. Carbon and hydrogen content, the two main elements for biofuel enhancement, were found to correlate with the organic components of both RWS (48.49, 7.15 wt.%) and SS (32.29, 4.06 wt.%). SS had a higher elemental composition of iron, calcium, and potassium than RWS. Both samples had a higher heating value of 13.98 to 21.01 MJ/kg and a lower heating value of 11.65 to 17.66 MJ/kg, a lesser energy potential than that of fossil fuels. The findings from these blends are relatively moderate due to the related lignocellulosic potential composition. The novel contribution of this research was to optimize the use of local waste materials as a new raw material for biofuel production that could serve as a sustainable fuel source.
Predicting defoliator abundance and defoliation measurements using Landsat‐based condition scores

Remote sensing imagery can provide critical information on the magnitude and extent of damage caused by forest pests and pathogens. However, monitoring short‐term changes in deciduous forest condition caused by defoliating insects is challenging and requires approaches that directly account for seasonal vegetation dynamics. We implemented a previously published harmonic modeling approach for forest condition monitoring in Google Earth Engine and systematically assessed the relative ability of condition change products generated using various model parameterizations for predicting pest abundances and defoliation during the 2016–2018 gypsy moth (Lymantria dispar) outbreak in southern New England. Our comparisons revealed that most models made reasonable predictions of changes in canopy condition and egg and larval abundances of L. dispar, indicating a strong correlation between our harmonic‐based estimates of condition change and defoliator activity. The greatest differences in predictive ability were in the spectral domain, with assessments based on Tasseled Cap Greenness, Simple Ratio, and the Enhanced Vegetation Index ranking among the top models, and the commonly used Normalized Difference Vegetation Index consistently exhibiting poorer performance. We also observed notable differences in the magnitude of scores for different baseline periods. Additionally, we found that Landsat‐based condition scores better explained larval abundance than egg mass counts, which have historically been used as a proxy for later‐season larval abundance, indicating that our remote sensing approach may be more accurate and cost‐effective for generating consistent retrospective assessments of L. dispar population abundance in addition to estimates of canopy damage. These findings provide important linkages between spectral changes detected using a harmonic modeling approach and biophysical aspects of defoliator activity, with potential to extend monitoring and prediction to regional or even continental scales.
Does Lobbying Affect Bill Advancement? Evidence from Three State Legislatures

Many studies consider the effect of lobbying on the behavior of individual legislators, but few studies demonstrate a relationship between lobbying and the ultimate dispositions of bills by the legislature. One challenge to establishing this latter relationship is data scarcity, as few legislatures systematically collect and publish information on organized interests’ lobbying activities on each bill. We provide new insights on lobbying by using data from Colorado, Nebraska, and Wisconsin that records the positions organized interests take on proposals in those states’ legislatures. We find that organized interests’ lobbying predicts outcomes, especially when lobbying is directed against a proposal. We also use our data to test whether lobbying succeeds by building support among legislators (i.e., vote buying) or by affecting a proposal’s advancement through the legislative process (i.e., agenda control). We find that lobbying does not buy the votes of legislators on the committees of jurisdiction for each bill, but lobbying does strongly predict what bills make it onto the agenda. Our findings contribute to ongoing discussions about money and politics, bias in representation, and legislator behavior.
Deep Metric Learning for Multi-Label and Multi-Object Image Retrieval

SUMMARY Content-based image retrieval has been a hot topic among computer vision researchers for a long time. There have been many advances over the years, one of the recent ones being deep metric learning, inspired by the success of deep neural networks in many machine learning tasks. The goal of metric learning is to extract good high-level features from image pixel data using neural networks. These features provide useful abstractions, which can enable algorithms to perform visual comparison between images with human-like accuracy. To learn these features, supervised information of image similarity or relative similarity is often used. One important issue in deep metric learning is how to deﬁne similarity for multi-label or multi-object scenes in images. Traditionally, pairwise similarity is deﬁned based on the presence of a single common label between two images. However, this deﬁnition is very coarse and not suitable for multi-label or multi-object data. Another common mistake is to completely ignore the multiplicity of objects in images, hence ignoring the multi-object facet of certain types of datasets. In our work, we propose an approach for learning deep image representations based on the relative similarity of both multi-label and multi-object image data. We introduce an intuitive and effective similarity metric based on the Jaccard similarity coe ﬃ cient, which is equivalent to the intersection over union of two label sets. Hence we treat similarity as a continuous, as opposed to discrete quantity. We incorporate this similarity metric into a triplet loss with an adaptive margin, and achieve good mean average precision on image retrieval tasks. We further show, using a recently proposed quantization method, that the resulting deep feature can be quantized whilst preserving similarity. We also show that our proposed similarity metric performs better for multi-object images than a previously proposed cosine similarity-based metric. Our proposed method outperforms several state-of-the-art methods on two benchmark datasets.
Lattice and magnetic instabilities in CaFe$_{2}$As$_{2}$

Neutron diffraction measurements of a high quality single crystal of CaFe2As2 are reported. A sharp transition was observed between the high temperature tetragonal and low temperature orthorhombic structures at TS = 172.5K (on cooling) and 173.5K (on warming). Coincident with the structural transition we observe a rapid, but continuous, ordering of the Fe moments, in a commensurate antiferromagnetic structure is observed, with a saturated moment of 0.80(5)muB/Fe directed along the orthorhombic a-axis. The hysteresis of the structural transition is 1K between cooling and warming and is consistent with previous thermodynamic, transport and single crystal x-ray studies. The temperature onset of magnetic ordering shifts rigidly with the structural transition providing the clearest evidence to date of the coupling between the structural and magnetic transitions in this material and the broader class of iron arsenides.
Structure-Free Broadcast Scheduling for Duty-Cycled Multihop Wireless Sensor Networks

Broadcasting is an essential operation in wireless networks for disseminating the message from the source node to all other nodes. Unfortunately, the problem of Minimum Latency Broadcast Scheduling (MLBS) in duty-cycled wireless sensor networks is not well studied. In existing works, the construction of broadcast tree and the scheduling of transmissions are conducted separately, where a tree-based structure is used as the input of the scheduling algorithm. Relying on a pre-determined tree may result in a much large latency even using the optimal scheduling method. Thus, the MLBS problem in duty-cycled WSNs without the above limitation is investigated in this paper. First, to avoid relying on a pre-determined structure, a two-step scheduling algorithm is proposed to construct the broadcast tree and compute a collision-free schedule simultaneously. To the best of our knowledge, this is the first work that can integrate these two kinds of operations together. Second, a novel transmission mode, i.e., concurrent broadcasting, is first introduced for wireless networks and several techniques are designed to further improve the broadcast latency. Third, the multiple messages broadcasting and all-to-all broadcasting algorithms, which can generate a series of broadcast schedules independently without a pre-determined tree, are also proposed by taking care of the collisions in both the current and the previous broadcast schedules. Finally, the theoretical analysis and experimental results demonstrate the efficiency of the proposed algorithms in terms of latency.
Evaluating zooplankton in traditional and split‐pond systems for raising golden shiners,
 
 Notemigonus crysoleucas

We hypothesize for golden shiners, Notemigonus crysoleucas , raised in split-ponds (SPS), that the waste treatment unit (WTU) would be a zooplankton refuge. To examine this hypothesis, a 6-week study was conducted in six traditional earthen ponds (TEP) and six SPS (each 0.04 ha) stocked with adult golden shiners at 450 kg of fish/ha. Fish were fed a commercial feed at 3% body weight daily in three ponds (FED) of each pond type, while in the remaining ponds fish had access to natural foods only (UNF). Zooplankton samples were collected daily for five consecutive days from three locations in each TEP and from three locations each within the fish culture unit (FCU) and WTU of SPS. Net yield and survival were not significantly different among the treatment groups. Survival was severely impacted by depredation from birds and herpetofauna. Fish in SPS-UNF ponds had lower condition factors, relative weight, whole-body fats, and gonadosomatic index compared to the other treatment groups. Zooplankton number/mL were significantly higher in the TEP (both FED and UNF) when compared to other treatment groups. There was not enough evidence that the WTU being devoid of fish may serve as a refuge for larger zooplankton. distribution. The present study was conducted over 42 days in late spring to compare zooplankton composition and distribution in experimental TEP and SPS used to raise golden shiners. The focus of this study was to test the hypothesis that the WTU of the SPS would become a plankton refuge and therefore would have higher zooplankton densities than TEP. If true, this study would provide a basis to optimize SPS design to raise fish species heavily relying on natural foods. Water temperature and precipitation were recorded daily during the study to determine appropriate days for sampling zooplankton. The spring rains and warmer water temperatures contributed to the zooplankton populations becoming established in ponds. Rotifer populations are the first to appear followed by microcrustaceans nauplii and then finally the microcrustaceans including copepods, cladocerans, and ostracods (Ludwig, 1989). In this study, rotifers were the numerically dominant group suggesting the zooplankton populations were just beginning to be established in the ponds. Also, it has been observed that in culture ponds, rotifers are present in larger numbers regardless of fish presence (Ludwig, 1989).