Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating sperm quality characteristics obtained through the female teaser method in native chicken breeds

<p class="MDPI17abstract"><strong>Objective: </strong>The quality and quantity of chicken sperm are critical factors influenced by the semen collection method<strong>. </strong>Therefore, this study aims to evaluate the sperm quality obtained from three native chicken breeds using the female teaser method. </p><p class="MDPI17abstract"><strong>Methods: </strong>These three native chicken breeds are Arabic, Birma, and Kampung Unggul Balitbangtan (KUB) chickens. Each breed comprised a group of three roosters, and the semen collection was performed ten times. Macroscopic and microscopic evaluations were conducted to assess the chicken sperm. The collected data were analyzed using Analysis of Variance (ANOVA) followed by Duncan's multiple range test (DMRT). <strong></strong></p><p class="MDPI17abstract"><strong>Result: </strong>The results of this study showed significant differences (P<0.05) in the sperm volume among the chicken breeds, with Birma (0.51 ml) and KUB chickens (0.60 ml) exhibiting distinct volumes compared to Arabic chicken (0.25 ml). Generally, the chicken sperm exhibited a milky white color and thick consistency. Microscopic evaluation yielded a mass motility rating of 3+. Meanwhile, individual motility and viability did not exhibit significant differences (P>0.05) among the three native chicken breeds. Abnormalities displayed significant variations (P<0.05), with Birma chicken showing the highest abnormality rate at 9.77%± 0.28. Sperm concentration did not exhibit significant differences (P>0.05), with the highest concentration observed in Arabic chicken at 4265.33±59.84 (x10<sup>6</sup> cells/ml). However, total sperm count and total motile sperm count exhibited significant variations (P<0.05), with the highest values recorded in KUB chicken at 2241.82±264.13 (x10<sup>6</sup> cells) and 1936.27±169.85 (x10<sup>6</sup> cells), respectively. <strong></strong></p><p class="MDPI17abstract"><strong>Conclusions: </strong>In conclusion, the semen collection method using the female teaser yielded native chicken sperm with high quality and quantity and meets the required standards for successful insemination. This method holds potential and is recommended for application in native chicken breeding programs. <strong></strong></p>
The Impact of Gender Based Violence on Women Life in Monduli District, Tanzania

Gеndеr-basеd violence (GBV) remains a pervasive issue in Tanzania, with manifestations including physical, sexual, psychological, and socioeconomic violence. Despite efforts by the government, GBV continues to afflict the community, particularly affecting women in the Masa society who face discrimination in education, legal status, cultural pеrspеctivеs, and economics. This paper assesses the impact of GBV on women’s lives in Moduli District, focusing on current forms of violence, women’s perceptions, and the mechanisms еmployеd by local government authoritiеs to addrеss GBV. Drawing on the Radical Fеminist Paradigm Theory and Psychoanalytic Theory, the study еxplorеs social rеlations through the lеns of gеndеr and еxaminеs the unеqual powеr dynamics bеtwееn mеn and women in patriarchal sociеtiеs. A casе study dеsign is adoptеd to invеstigatе the issue thoroughly, using both qualitativе and quantitativе approachеs for data analysis. Contеnt analysis is еmployеd for qualitativе data, whilе dеscriptivе statistics arе usеd to analyzе quantitativе data. Thе study rеvеals that prеvalеnt forms of GBV in Moduli District includе physical violence, rapе, dowry-rеlatеd violence, forcеd prеgnancy, vеrbal insults, forcеd marriagе, dеfamation, and intimidation in various sеttings. Womеn pеrcеivе GBV as rеstricting social and еconomic participation, еmploymеnt, financial rеsourcеs, autonomy, and control. Thе mechanisms еmployеd for rеsolving GBV disputеs includе litigation, gеndеr mainstrеaming stratеgiеs, intimidation, and the involvеmеnt of еldеrs. Thе paper concludеs with rеcommеndations for local government intеrvеntion, еmphasizing community-widе awarеnеss campaigns on the short- and long-tеrm еffеcts of GBV, supplеmеntеd by legal mеasurеs, gеndеr mainstrеaming, and the involvеmеnt of еldеrs. Addrеssing thеsе challеngеs is crucial to mitigating the impact of GBV on women in Moduli District, including issuеs of confidеncе, moral dеcay, family sеparation, and mеntal and еmotional trauma.
Pyroclimatic classification of Mediterranean and mountain landscapes of south-eastern France

Fire risk is expected to increase in the Mediterranean Basin like in many areas worldwide. Climate is likely the main driver of fire activity by conditioning fuel dryness and fire weather. However fire-climate relationships are conditioned by other environmental dimensions like fuel structure (composition and spatial arrangement of flammable vegetation) and human activities. Therefore assessing how climate controls fire activity in heavily anthropized landscapes like European Mediterranean regions requires to design analyses in appropriate geographic units to encompass the dominant fire drivers. We aimed to assess how spatiotemporal patterns of both fire activity and climate structured south-eastern France into homogeneous geographic unit which we defined as ‘pyroclimatic’ regions. We performed a pyroclimatic classification of Mediterranean and mountain areas of south-eastern France at 2 km resolution from the national fire database and daily atmospheric parameters over 1973-2009. This classification was based on multidimensional and clustering analyses. South-eastern France is characterized by three main ‘pyroclimatic’ regions and ten sub-regions from high fire-prone maritime mountains to moderate fire-prone hot lowlands and low fire-prone inner moist mountains. These geographic units are discriminated from each other by fire activity, fire seasonality, fire weather and their recent evolution. We demonstrated that fire activity and fire weather of south-eastern France are highly dynamic in space and time. Characterizing pyroclimatic regions offers new regional perspectives of fire management and policy because two areas having similar fire weather, fire regime and recent temporal trends would benefit for specific attention.
Confirming the Receipts of International Tourism in Indonesia after the COVID-19 Pandemic: Analyzed with Macroeconomic Indicators

This study aims to analyze International Tourism Receipts in Indonesia with the variables of International Trade, Inflation, and Exchange Rates during and after the COVID-19 pandemic. The analysis technique used to answer the problem is regression analysis using the Ordinary Least Squares (OLS) method. This type of research data uses secondary data obtained from the World Bank, Central Statistics Agency, and Bank Indonesia during the 2002-2022 period. The results of research analysis show that 1) the International Trade variable has a significant negative effect on International Tourism Receipts in Indonesia during and after the COVID-19 pandemic. The stability of international trade fluctuates, tends to decrease, but after the COVID-19 pandemic and the relaxation of social distancing policies, there has been an increase in international tourism. 2) The Inflation variable has a significant negative effect on International Tourism Receipts in Indonesia. A higher inflation rate increases living and travel costs, then reduces tourist interest. 3) The exchange rate variable has a significant and positive effect toward international tourism receipts. The increase of dollar exchange rate against the rupiah, will increase tourist interest in Indonesia. The implications of the results of this research are important for stakeholders and tourism sector companies so that they can continuously increase International Tourism Receipts in Indonesia through keeping macroeconomic indicators consisting of International Trade, Inflation and Exchange in Indonesia.
Effective mmWave Radar Object Detection Pretraining Based on Masked Image Modeling

With the advancement of environmental perception technology, millimeter-wave (mmWave) radar is emerging as a predominant sensor. While deep learning has facilitated the development of mmWave radar object detection (ROD) techniques, mmWave ROD suffers from datasets because the annotation of mmWave datasets is inherently more complex. Motivated by masked image modeling (MIM), this article proposes a novel pretraining method for ROD to address the limitations posed by datasets. This study conducts masking operations on mmWave radar images from both spatial and temporal perspectives, followed by a straightforward image reconstruction proxy task. To the best of authors’ knowledge, our method represents the inaugural application of the MIM self-supervision method to ROD tasks. Additionally, we designed a lightweight self-supervised ROD network (SS-RODNet). Numerous ablation experiments have demonstrated the effectiveness of the proposed method. The pretrained SS-RODNet attains comparable results to the state-of-the-art (SOTA) on CRUW and CARRADA datasets with fewer parameters and floating-point operations per second (FLOPs).
Spatially Recalibrated Convolutional Neural Network for Vehicle Type Recognition

Vehicle Type Recognition (VTR) is a significant segment within the vehicle recognition field. It provides an alternative identification method aside from license plate recognition and vehicle make and model recognition. Most of the recent studies use Convolutional Neural Networks (CNNs) to perform VTR. However, the feature responses obtained from CNNs are not recalibrated based on saliency and this hinders the classification performance. In this study, we propose a Spatial Attention Module (SAM) that is compatible with the existing CNNs. We aim to exploit the spatial relationship between feature responses by scaling them according to their relative importance to increase classification accuracy. The results reveal the exceptional performance of SAM on Beijing Institute of Technology (BIT)-Vehicle, Stanford Cars and web-nature Comprehensive Cars (CompCarsWeb) with 96.92%, 84.48% and 95.96% accuracies, respectively. A qualitative inspection of the learned feature embedding suggests the high cohesivity of the features within the group. Furthermore, an ablation study is conducted to justify the hyperparameters of choice for SAM. SAM is also modular where it is highly compatible with other CNNs and it leads to considerable performance improvement. A comparison with existing attention modules suggests our proposal prevails in the VTR application. The inference times of 1 ms and 10 ms for CaffeNet-SAM and ResNet-SAM also make them suitable for real-time classification tasks.
Sustainable Management Of Natural Resources Mathematical Models And Methods

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Effect of Electrical Stimulation on PC12 Cells Cultured in Different Hydrogels: Basis for the Development of Biomaterials in Peripheral Nerve Tissue Engineering

Extensive damage to peripheral nerves is a health problem with few therapeutic alternatives. In this context, the development of tissue engineering seeks to obtain materials that can help recreate environments conducive to cellular development and functional repair of peripheral nerves. Different hydrogels have been studied and presented as alternatives for future treatments to emulate the morphological characteristics of nerves. Along with this, other research proposes the need to incorporate electrical stimuli into treatments as agents that promote cell growth and differentiation; however, no precedent correlates the simultaneous effects of the types of hydrogel and electrical stimuli. This research evaluates the neural differentiation of PC12 cells, relating the effect of collagen, alginate, GelMA, and PEGDA hydrogels with electrical stimulation modulated in four different ways. Our results show significant correlations for different cultivation conditions. Electrical stimuli significantly increase neural differentiation for specific experimental conditions dependent on electrical frequency, not voltage. These backgrounds allow new material treatment schemes to be formulated through electrical stimulation in peripheral nerve tissue engineering.
Predicting the Potential Distribution of the Szechwan Rat Snake (Euprepiophis perlacea) and Its Response to Climate Change in the Yingjing Area of the Giant Panda National Park

Simple Summary This study employs maxent models to investigate the impact of climate change on the potential distribution of the Szechwan rat snake (Euprepiophis perlacea) in the Yingjing Area of the Giant Panda National Park. The analysis reveals the significant effects of distance from the streams and slope of the geographic distribution of E. perlacea. Furthermore, this study indicates a non-significant reduction in the potential distribution area for the species by the 2050s, which is attributed to reduced anthropogenic activities and habitat fragmentation within the Yingjing Area of the Giant Panda National Park. These findings validate the development of conservation guidelines for E. perlacea. More research is needed to identify suitable protected areas and wildlife corridors for E. perlacea across its distribution regions, thus enhancing its conservation prospects. Abstract Climate change is a significant driver of changes in the distribution patterns of species and poses a threat to biodiversity, potentially resulting in species extinctions. Investigating the potential distribution of rare and endangered species is crucial for understanding their responses to climate change and for the conservation of biodiversity and ecosystem management. The Szechwan rat snake (Euprepiophis perlacea) is an endemic and endangered species co-distributed with giant pandas, and studying its potential distribution contributes to a better understanding of the distribution pattern of endangered species. In this study, we confirmed seven presence points of this species in the Yingjing Area of the Giant Panda National Park, and selected eleven key factors to predict the potential distribution of E. perlacea under current and future scenarios using MaxEnt models. Our study consistently achieved AUC values exceeding 0.79, meeting the precision requirements of the models. The results indicated that the high potential distribution area of E. perlacea is mainly located near Yunwu mountain and the giant panda rewilding and reintroduction base, accounting for approximately 12% of the protected area. Moreover, we identified the primary environmental factors influencing the distribution of E. perlacea as the distance from streams and the slope degree, with their contribution rates exceeding 41% and 31%, respectively. In comparison to the current scenario, the potential habitat range for E. perlacea did not show an overall reduction in the context of future climate scenarios. To ensure the long-term preservation of E. perlacea, it is advisable to validate its actual distribution based on the models’ results. Particular attention should be given to safeguarding its core distribution areas and raising awareness among residents within the potential distribution range about the conservation of E. perlacea.
The Impact of Simulation-Based Training in Cardiovascular Medicine: A Systematic Review

Cardiovascular medicine and practice in recent times have evolved as complex procedures are performed to manage difficult cases. The majority of these interventions are done percutaneously in order to minimize patient risk. Additionally, training specialist in handling these interventions require a lot of exposure to them; as such, patients are at higher risk of errors and complications from trainees before attaining expertise. In order to avoid these possible risks to patients and ensure their safety, using simulation commonly in cardiovascular specialist education is a possible trend in the future. This article aims to review randomized controlled trials that were performed in cardiology and vascular medicine regarding the use of simulating models to transfer skills to trainees. This study is a systematic review that includes publications dated from 2010 from any country and only in English. The search involved several combinations of search terms from medical subject headings (MeSH). Keywords in the title, abstract, and text for the population, intervention, control, and outcomes were first done in a pilot search to establish the sensitivity of the search strategy. Studies were searched in PubMed, Medline, Cochrane Library, Embase, CINAHL, and Hirani. Data were presented in the PRISMA flowchart and tabular form. A total of 389 studies were obtained from five databases using the search strategies. Eighty-nine studies were excluded for duplication. The total number of studies that did not meet the inclusion criteria was 269, and they were excluded based on abstract and title screening. Another 18 studies were excluded based on full-text screening. In this study, 13 articles were selected ranging from 2011 to 2022. The majority of the outcomes of the study demonstrated that simulation tutoring complements traditional methods of training. Countries of publication were the United States of America, Canada, Italy, Korea, California, Ireland, Germany, Belgium, Switzerland, United Kingdom, Netherlands, and France. Procedures simulated include coronary angiography, transseptal catheterization, cardiopulmonary resuscitation, ultrasound-guided radial artery cannulation, diagnostic angiograms, coiled carotid terminus aneurysms in the setting of subarachnoid hemorrhage, middle cerebral artery embolectomies, renal artery angioplasty/stenting, endovascular aneurysm repair, transvenous pacing wire, intra-aortic balloon pump, and pericardiocentesis. Despite the accredited drawback of availability and cost noted with simulation-based education, there is evidence that it offers many advantages compared to traditional teaching methods. From this study, simulation-based teaching has been shown to effectively transfer skills to trainees especially when used as an adjunct to the apprenticeship method. As a result, we recommend that virtual reality education should be integrated with real-life teaching in modern cardiovascular modules as this will help ensure early skill transfer while maintaining patient safety.
Quantifying fire-specific smoke exposure and health impacts.

Rapidly changing wildfire regimes across the Western United States have driven more frequent and severe wildfires, resulting in wide-ranging societal threats from wildfires and wildfire-generated smoke. However, common measures of fire severity focus on what is burned, disregarding the societal impacts of smoke generated from each fire. We combine satellite-derived fire scars, air parcel trajectories from individual fires, and predicted smoke PM2.5 to link source fires to resulting smoke PM2.5 and health impacts experienced by populations in the contiguous United States from April 2006 to 2020. We quantify fire-specific accumulated smoke exposure based on the cumulative population exposed to smoke PM2.5 over the duration of a fire and estimate excess asthma-related emergency department (ED) visits as a result of this exposure. We find that excess asthma visits attributable to each fire are only moderately correlated with common measures of wildfire severity, including burned area, structures destroyed, and suppression cost. Additionally, while recent California fires contributed nearly half of the country's smoke-related excess asthma ED visits during our study period, the most severe individual fire was the 2007 Bugaboo fire in the Southeast. We estimate that a majority of smoke PM2.5 comes from sources outside the local jurisdictions where the smoke is experienced, with 87% coming from fires in other counties and 60% from fires in other states. Our approach could enable broad-scale assessment of whether specific fire characteristics affect smoke toxicity or impact, inform cost-effectiveness assessments for allocation of suppression resources, and help clarify the growing transboundary nature of local air quality.
Sensor Response-Based Localization Using Spatial Correlation of Nongeotagged Data

Sensor devices in future wireless communication systems such as beyond fifth generation (Beyond 5G) and sixth generation (6G) require highly accurate location information. Owing to high power consumption and cost, global navigation satellite system (GNSS) receivers may not be installed on sensor devices, requiring the localization of sensor devices on a wireless sensor network (WSN). In many WSN applications, a spatially dense sensor installation is required to achieve satisfactory coverage. When object detection-type sensor devices are installed at high density, the responses of spatially proximate sensors are highly correlated. In other words, these sensor responses indirectly include location information. Based on this consideration, we proposed a sensor localization method using the spatial correlation of nongeotagged sensor response data and evaluated its performance. Our method enables location estimation from the response data obtained during environmental monitoring, even for sensors that are not equipped with range functions. The simulation experiments showed that a more accurate sensor localization is possible with an error of 1 m using a wider sensor detection range, even with rough proximity pair ratio settings. In addition, we verified that there is a tradeoff between localizability and observability during environmental monitoring, such as the visualization of vehicle positions from sensor responses. Our proposed method may be applied to future urban environments with a large number of sensor devices installed for environmental monitoring.
Effects of Dextran on the Gel Properties of Faba Bean Protein Isolates Prepared Using Different Processes

The properties of faba bean (Vicia faba L.) protein isolate (FPI) gels depend on their starting protein material and can be modulated by the addition of polysaccharides. In order to investigate the interplay between these two factors, commercial FPI (FPI1) and FPI prepared in-house (FPI2) were used to fabricate glucono-delta-lactone-induced gels, with or without dextran (DX) addition. FPI1 exhibited lower solubility in water and a larger mean particle size, likely because it experienced extensive degradation due to the intense conditions involved in its preparation. The FPI1 gel showed a similar water-holding capacity as the FPI2 gel; however, its hardness was lower and viscoelasticity was higher. After DX addition, the hardness of both FPI gels decreased, while their water-holding capacity increased. Interestingly, DX addition decreased the viscoelasticity of the FPI1 gel but enhanced the viscoelasticity of the FPI2 gel. The microstructural analysis demonstrated that the density of the aggregation network decreased in the FPI1 gel after DX addition but increased in the FPI2 gel. This was consistent with the changes observed in the dominant protein interaction forces in these gels after DX addition. Overall, these findings have the potential to guide ingredient selection for the tailored preparation of FPI gels.