Numerical Analysis on Temperature Distribution in a Single Cell of PEFC Operated at Higher Temperature by1D Heat Transfer Model and 3D Multi-Physics Simulation Model

This study is to understand the impact of operating conditions, especially initial operation temperature (Tini) which is set in a high temperature range, on the temperature profile of the interface between the polymer electrolyte membrane (PEM) and the catalyst layer at the cathode (i.e., the reaction surface) in a single cell of polymer electrolyte fuel cell (PEFC). A 1D multi-plate heat transfer model based on the temperature data of the separator measured using the thermograph in a power generation experiment was developed to evaluate the reaction surface temperature (Treact). In addition, to validate the proposed heat transfer model, Treact obtained from the model was compared with that from the 3D numerical simulation using CFD software COMSOL Multiphysics which solves the continuity equation, Brinkman equation, Maxwell-Stefan equation, Butler-Volmer equation as well as heat transfer equation. As a result, the temperature gap between the results obtained by 1D heat transfer model and those obtained by 3D numerical simulation is below approximately 0.5 K. The simulation results show the change in the molar concentration of O2 and H2O from the inlet to the outlet is more even with the increase in Tini due to the lower performance of O2 reduction reaction. The change in the current density from the inlet to the outlet is more even with the increase in Tini and the value of current density is smaller with the increase in Tini due to the increase in ohmic over-potential and concentration over-potential. It is revealed that the change in Treact from the inlet to the outlet is more even with the increase in Tini irrespective of heat transfer model. This is because the generated heat from the power generation is lower with the increase in Tini due to the lower performance of O2 reduction reaction.

Temperature characterizations of silica asymmetric Mach–Zehnder interferometer chip for quantum key distribution

Quantum key distribution(QKD)system based on passive silica planar lightwave circuit(PLC)asymmetric Mach–Zehnder interferometers(AMZI)is characterized with thermal stability,low loss and sufficient integration scalability.However,waveguide stresses,both intrinsic and temperature-induced stresses,have significant impacts on the stable operation of the system.We have designed silica AMZI chips of 400 ps delay,with bend waveguides length equalized for both long and short arms to balance the stresses thereof.The temperature characteristics of the silica PLC AMZI chip are studied.The interference visibility at the single photon level is kept higher than 95%over a wide temperature range of 12℃.The delay time change is 0.321 ps within a temperature change of 40℃.The spectral shift is 0.0011 nm/0.1℃.Temperature-induced delay time and peak wavelength variations do not affect the interference visibility.The experiment results demonstrate the advantage of being tolerant to chip temperature fluctuations.

El Niño and the AMO Sparked the Astonishingly Large Margin of Warming in the Global Mean Surface Temperature in 2023

In 2023,the majority of the Earth witnessed its warmest boreal summer and autumn since 1850.Whether 2023 will indeed turn out to be the warmest year on record and what caused the astonishingly large margin of warming has become one of the hottest topics in the scientific community and is closely connected to the future development of human society.We analyzed the monthly varying global mean surface temperature(GMST)in 2023 and found that the globe,the land,and the oceans in 2023 all exhibit extraordinary warming,which is distinct from any previous year in recorded history.Based on the GMST statistical ensemble prediction model developed at the Institute of Atmospheric Physics,the GMST in 2023 is predicted to be 1.41℃±0.07℃,which will certainly surpass that in 2016 as the warmest year since 1850,and is approaching the 1.5℃ global warming threshold.Compared to 2022,the GMST in 2023 will increase by 0.24℃,with 88%of the increment contributed by the annual variability as mostly affected by El Niño.Moreover,the multidecadal variability related to the Atlantic Multidecadal Oscillation(AMO)in 2023 also provided an important warming background for sparking the GMST rise.As a result,the GMST in 2023 is projected to be 1.15℃±0.07℃,with only a 0.02℃ increment,if the effects of natural variability—including El Niño and the AMO—are eliminated and only the global warming trend is considered.

The Influence of Climate Change and Variability on Spatio-Temporal Rainfall and Temperature Distribution in Zanzibar

Climate change has resulted in serious social-economic ramifications and extremely catastrophic weather events in the world, Tanzania and Zanzibar in particular, with adaptation being the only option to reduce impacts. The study focuses on the influence of climate change and variability on spatio-temporal rainfall and temperature variability and distribution in Zanzibar. The station observation datasets of rainfall, Tmax and Tmin acquired from Tanzania Meteorological Authority (TMA) and the Coordinated Regional Climate Downscaling Experiment program (CORDEX) projected datasets from the Regional climate model HIRHAM5 under driving model ICHEC-EC-EARH, for the three periods of 1991-2020 used as baseline (HS), 2021-2050 as near future (NF) and 2051-2080 far future (FF), under two representative concentration pathways (RCP) of 4.5 and 8.5, were used. The long-term observed Tmax and Tmin were used to produce time series for observing the nature and trends, while the observed rainfall data was used for understanding wet and dry periods, trends and slope (at p ≤ 0.05) using the Standardized Precipitation Index (SPI) and the Mann Kendall test (MK). Moreover, the Quantum Geographic Information System (QGIS) under the Inverse Distance Weighting (IDW) interpolation techniques were used for mapping the three decades of 1991-2000 (hereafter D1), 2001-2010 (hereafter D2) and 2011-2020 (hereafter D3) to analyze periodical spatial rainfall distribution in Zanzibar. As for the projected datasets the Climate Data Operator Commands (CDO), python scripts and Grid analysis and Display System (GrADS) soft-wares were used to process and display the results of the projected datasets of rainfall, Tmax and Tmin for the HS, NF and FF, respectively. The results show that the observed Tmax increased by the rates of 0.035℃ yr-1 and 0.0169℃ yr-1, while the Tmin was increased by a rate of 0.064℃ yr-1 and 0.104℃ yr-1 for Unguja and Pemba, respectively. The temporal distribution of wetness and dryness indices showed a climate shift from near normal to moderate wet during 2005 at Zanzibar Airport, while normal to moderately dry conditions, were observed in Pemba at Matangatuani. The decadal rainfall variability and distributions revealed higher rainfall intensity with an increasing trend and good spatial distribution in D3 from March to May (MAM) and October to December (OND). The projected results for Tmax during MAM and OND depicted higher values ranging from 1.7℃ - 1.8℃ to 1.9℃ - 2.0℃ and 1.5℃ to 2.0℃ in FF compared to NF under both RCPs. Also, higher Tmin values of 1.12℃ - 1.16℃ was projected in FF for MAM and OND under both RCPs. Besides, the rainfall projection generally revealed increased rainfall intensity in the range of 0 - 25 mm for Pemba and declined rainfall in the range of 25 - 50 mm in Unguja under both RCPs in perspectives of both NF and FF. Conclusively the study has shown that the undergoing climate change has posed a significant impact on both rainfall and temperature spatial and temporal distributions in Zanzibar (Unguja and Pemba), with Unguja being projected to have higher rainfall deficits while increasing rainfall strengths in Pemba. Thus, the study calls for more studies and formulation of effective adaptation, strategies and resilience mechanisms to combat the projected climate change impacts especially in the agricultural sector, water and food security.

Record-breaking High-temperature Outlook for 2023: An Assessment Based on the China Global Merged Temperature(CMST) Dataset

According to the latest version(version 2.0) of the China global Merged Surface Temperature(CMST2.0) dataset, the global mean surface temperature(GMST) in the first half of 2023 reached its third warmest value since the period of instrumental observation began, being only slightly lower than the values recorded in 2016 and 2020, and historically record-breaking GMST emerged from May to July 2023. Further analysis also indicates that if the surface temperature in the last five months of 2023 approaches the average level of the past five years, the annual average surface temperature anomaly in 2023 of approximately 1.26°C will break the previous highest surface temperature, which was recorded in 2016of approximately 1.25°C(both values relative to the global pre-industrialization period, i.e., the average value from 1850 to1900). With El Ni?o triggering a record-breaking hottest July, record-breaking average annual temperatures will most likely become a reality in 2023.

A bHLH transcription factor,CsSPT,regulates high-temperature resistance in cucumber

High-temperature stress threatens the growth and yield of crops. Basic helix-loop-helix(bHLH) transcription factors(TFs) have been shown to play important roles in regulating high-temperature resistance in plants. However, the bHLH TFs responsible for high-temperature tolerance in cucumbers have not been identified. We used transcriptome profiling to screen the high temperature-responsive candidate bHLH TFs in cucumber. Here, we found that the expression of 75 CsbHLH genes was altered under high-temperature stress. The expression of the CsSPT gene was induced by high temperatures in TT(Thermotolerant) cucumber plants. However, the Csspt mutant plants obtained by the CRISPR-Cas9 system showed severe thermosensitive symptoms, including wilted leaves with brown margins and reduced root density and cell activity.The Csspt mutant plants also exhibited elevated H_(2)O_(2) levels and down-regulated photosystem-related genes under normal conditions.Furthermore, there were high relative electrolytic leakage(REC), malondialdehyde(MDA), glutathione(GSH), and superoxide radical(O_(2)^(·-)) levels in the Csspt mutant plants, with decreased Proline content after the high-temperature treatment. Transcriptome analysis showed that the photosystem and chloroplast activities in Csspt mutant plants were extremely disrupted by the high-temperature stress compared with wildtype(WT) plants. Moreover, the plant hormone signal transduction, as well as MAPK and calcium signaling pathways were activated in Csspt mutant plants under high-temperature stress. The HSF and HSP family genes shared the same upregulated expression patterns in Csspt and WT plants under high-temperature conditions. However, most bHLH, NAC, and bZIP family genes were significantly down-regulated by heat in Csspt mutant plants. Thus, these results demonstrated that CsSPT regulated the high-temperature response by recruiting photosynthesis components, signaling pathway molecules, and transcription factors. Our results provide important insights into the heat response mechanism of CsSPT in cucumber and its potential as a target for breeding heat-resistant crops.

Competitive oxidation behavior of Ni-based superalloy GH4738 at extreme temperature

A high thrust-to-weight ratio poses challenges to the high-temperature performance of Ni-based superalloys. The oxidation behavior of GH4738 at extreme temperatures has been investigated by isothermal and non-isothermal experiments. As a result of the competitive diffusion of alloying elements, the oxide scale included an outermost porous oxide layer (OOL), an inner relatively dense oxide layer (IOL), and an internal oxide zone (IOZ), depending on the temperature and time. A high temperature led to the formation of large voids at the IOL/IOZ interface. At 1200℃, the continuity of the Cr-rich oxide layer in the IOL was destroyed, and thus, spallation occurred. Extension of oxidation time contributed to the size of Al-rich oxide particles with the increase in the IOZ. Based on this finding,the oxidation kinetics of GH4738 was discussed, and the corresponding oxidation behavior at 900-1100℃ was predicted.

On the Thermal Distribution in Oncological Hyperthermia Treatments

The temperature is one of the principal controlling parameters of oncological hyperthermia. However, local heating forms a complicated thermal distribution in space and has developed over time, too. The decisional factors are the heterogeneity of the targeted volume, the electrolyte perfusions controlled by thermal homeostasis, and the spreading of the heat energy with time. A further complication is that the energy absorption sharply changes by depth, so the spatiotemporal development of the temperature distribution requires specialized methods to control. Most of the temperature imaging facilities (thermography, radiometry, electric impedance tomography, etc.) are less precise than the medical practice needs. In contrast, precise point sensing (like thermocouples, thermistors, and fluoroptical methods) is invasive and measures only a discrete point in the robustly changing thermal map. The two most precise thermal imaging methods, computer tomography, and magnetic resonance are expensive and have numerous technical complications. Our objective is to show the complexity of the temperature distribution inside the human body, and offer a relatively simple and cheap method to visualize its spatiotemporal development. A novel emerging technology, the application of ultrasound microbubble contrast agents is a promising method for solving complicated tasks of thermal distribution deep inside the living body. Noteworthy, the temperature distribution does not determine the full hyperthermia process, nonthermal effects make considerable impact, too. Additionally to the difficulties to measure the thermal heterogeneity during hyperthermia in oncology, numerous nonthermal processes, molecular and structural changes are triggered by the incoming electromagnetic energy, which presently has no spatiotemporal visualization technique. Microbubble imaging has a suitable spatiotemporal thermal resolution, and also it is sensitive to nonthermal effects. Its application for characterization of the modulated electrohyperthermia (mEHT) may open a new theranostic facility, using the synergy of the thermal and nonthermal effects of the radiofrequency delivered energy. This complex approach gives facility to follow the mEHT processes, and the proposed microbubble ultrasound imaging has a particularly promising advantage sensing and acting also nonthermally, having potential to characterize the thermally conditioned nonthermal electromagnetic effects in oncologic hyperthermia. The mEHT combined with microbubble ultrasound images could be a robust theranostic method against cancer.

Machine learning-assisted efficient design of Cu-based shape memory alloy with specific phase transition temperature

The martensitic transformation temperature is the basis for the application of shape memory alloys(SMAs),and the ability to quickly and accurately predict the transformation temperature of SMAs has very important practical significance.In this work,machine learning(ML)methods were utilized to accelerate the search for shape memory alloys with targeted properties(phase transition temperature).A group of component data was selected to design shape memory alloys using reverse design method from numerous unexplored data.Component modeling and feature modeling were used to predict the phase transition temperature of the shape memory alloys.The experimental results of the shape memory alloys were obtained to verify the effectiveness of the support vector regression(SVR)model.The results show that the machine learning model can obtain target materials more efficiently and pertinently,and realize the accurate and rapid design of shape memory alloys with specific target phase transition temperature.On this basis,the relationship between phase transition temperature and material descriptors is analyzed,and it is proved that the key factors affecting the phase transition temperature of shape memory alloys are based on the strength of the bond energy between atoms.This work provides new ideas for the controllable design and performance optimization of Cu-based shape memory alloys.

Federated Learning Model for Auto Insurance Rate Setting Based on Tweedie Distribution

In the assessment of car insurance claims,the claim rate for car insurance presents a highly skewed probability distribution,which is typically modeled using Tweedie distribution.The traditional approach to obtaining the Tweedie regression model involves training on a centralized dataset,when the data is provided by multiple parties,training a privacy-preserving Tweedie regression model without exchanging raw data becomes a challenge.To address this issue,this study introduces a novel vertical federated learning-based Tweedie regression algorithm for multi-party auto insurance rate setting in data silos.The algorithm can keep sensitive data locally and uses privacy-preserving techniques to achieve intersection operations between the two parties holding the data.After determining which entities are shared,the participants train the model locally using the shared entity data to obtain the local generalized linear model intermediate parameters.The homomorphic encryption algorithms are introduced to interact with and update the model intermediate parameters to collaboratively complete the joint training of the car insurance rate-setting model.Performance tests on two publicly available datasets show that the proposed federated Tweedie regression algorithm can effectively generate Tweedie regression models that leverage the value of data fromboth partieswithout exchanging data.The assessment results of the scheme approach those of the Tweedie regressionmodel learned fromcentralized data,and outperformthe Tweedie regressionmodel learned independently by a single party.

Low-energy-consumption temperature swing system for CO_(2) capture by combining passive radiative cooling and solar heating

Temperature-swing adsorption(TSA)is an effective technique for CO_(2) capture,but the temperature swing procedure is energy-intensive.Herein,we report a low-energy-consumption system by combining passive radiative cooling and solar heating for the uptake of CO_(2) on commercial activated carbons(CACs).During adsorption,the adsorbents are coated with a layer of hierarchically porous poly(vinylidene fluoride-co-hexafluoropropene)[P(VdF-HFP)HP],which cools the adsorbents to a low temperature under sunlight through radiative cooling.For desorption,CACs with broad absorption of the solar spectrum are exposed to light irradiation for heating.The heating and cooling processes are completely driven by solar energy.Adsorption tests under mimicked sunlight using the CACs show that the performance of this system is comparable to that of the traditional ones.Furthermore,under real sunlight irradiation,the adsorption capacity of the CACs can be well maintained after multiple cycles.The present work may inspire the development of new temperature swing procedures with little energy consumption.

Integrative biogeography: Validating hypotheses of species distribution

DEAR EDITOR,Biogeography is a scientific field dedicated to the investigation of the origins and distribution patterns of organisms,as well as predicting future alterations in their geographical distributions(Cox&Moore,2005).However,the majority of conclusions drawn within the field of biogeography are hypothetical.Rigorous testing of these biogeographic hypotheses remains a considerable challenge.This paper presents the concept of“integrative biogeography”,which emphasizes the experimental testing of biogeographic hypotheses through studies on geological history,as well as biotic and abiotic factors(Figure 1).

Absorptive root-multidimension strategy links air temperature and species distribution in a montane forest

Background: Air temperature affects absorptive root traits, which are closely related to species distribution.However, it is still unclear how air temperature regulates species distribution through changes in absorptive root traits. Seven functional traits of the absorptive roots of 240 individuals of 52 species, soil properties and air temperature were measured along an elevational gradient on Mt. Fanjingshan, Tongren City, Guizhou, and then the direct and indirect effects of these controls on species distribution were detected.Results: Absorptive roots adapted to air temperature with two strategies. The first strategy was positively associated with the specific root area(SRA) and specific root length(SRL) and was negatively associated with the root tissue density(RTD), representing the classic root economics spectrum(RES). The second strategy was represented by the trade-off between root diameter, mycorrhizal fungi colonization(MF) and SRL, representing the collaboration gradient with “do it yourself” resource uptake ranging from “outsourcing” to mycorrhizal resource uptake. Air temperature regulated species distribution in six ways: directly reducing species importance value;indirectly increasing the species importance value by reducing soil nitrogen content or increasing soil pH by reducing soil moisture inducing absorptive roots to change from “do it yourself” resource absorption to “outsourcing” resource absorption;indirectly decreasing the species importance value by decreasing soil moisture to change from“outsourcing”resource absorption to “do it yourself” resource absorption;indirectly increasing the species importance value with increasing soil pH by reducing soil moisture resulting in absorptive root traits turning into nutrient foraging traits;and indirectly decreasing the species importance value by promoting absorptive root traits to nutrient conservation traits.Conclusions: Absorptive root traits play a crucial role in the regulation of species distribution through multiapproaches of air temperature.

Non-intrusive temperature rise fault-identification of distribution cabinet based on tensor block-matching

In this study,a novel non-intrusive temperature rise fault-identification method for a distribution cabinet based on tensor block-matching is proposed.Two-stage data repair is used to reconstruct the temperature-field information to support the demand for temperature rise fault-identification of non-intrusive distribution cabinets.In the coarse-repair stage,this method is based on the outside temperature information of the distribution cabinet,using tensor block-matching technology to search for an appropriate tensor block in the temperature-field tensor dictionary,filling the target space area from the outside to the inside,and realizing the reconstruction of the three-dimensional temperature field inside the distribution cabinet.In the fine-repair stage,tensor super-resolution technology is used to fill the temperature field obtained from coarse repair to realize the smoothing of the temperature-field information inside the distribution cabinet.Non-intrusive temperature rise fault-identification is realized by setting clustering rules and temperature thresholds to compare the location of the heat source with the location of the distribution cabinet components.The simulation results show that the temperature-field reconstruction error is reduced by 82.42%compared with the traditional technology,and the temperature rise fault-identification accuracy is greater than 86%,verifying the feasibility and effectiveness of the temperature-field reconstruction and temperature rise fault-identification.

Translocation and Distribution of Carbon-Nitrogen in Relation to Rice Yield and Grain Quality as Affected by High Temperature at Early Panicle Initiation Stage

Due to climate change, extreme heat stress events have become more frequent, adversely affecting rice yield and grain quality. The accumulation and translocation of dry matter and nitrogen substances are essential for rice yield and grain quality. To assess the impact of high temperature stress(HTS) at the early panicle initiation(EPI) stage on the accumulation, transportation, and distribution of dry matter and nitrogen substances in various organs of rice, as well as the resulting effects on rice yield and grain quality, pot experiments were conducted using an indica rice cultivar Yangdao 6(YD6) and a japonica rice cultivar Jinxiangyu 1(JXY1) under both normal temperature(32 ℃/26 ℃) and high temperature(38 ℃/29 ℃) conditions. The results indicated that exposure to HTS at the EPI stage significantly decreased rice yield by reducing spikelet number per panicle, grain-filling rate, and grain weight. However, it improved the nutritional quality of rice grains by increasing protein and amylose contents. The reduction in nitrogen and dry matter accumulation accounted for the changes in spikelet number per panicle, grain-filling rate, and grain size. Under HTS, the decrease in nitrogen accumulation accompanied by the reduction in dry matter may be due to the down-regulation of leaf net photosynthesis and senescence, as evidenced by the decrease in nitrogen content. Furthermore, the decrease in sink size limited the translocation of dry matter and nitrogen substances to grains, which was closely related to the reduction in grain weight and the deterioration of grain quality. These findings significantly contribute to our understanding of the mechanisms of HTS on grain yield and quality formation from the perspective of dry matter and nitrogen accumulation and translocation. Further efforts are needed to improve the adaptability of rice varieties to climate change in the near future.

Neural stem cell-derived exosomes promote mitochondrial biogenesis and restore abnormal protein distribution in a mouse model of Alzheimer's disease

Mitochondrial dysfunction is a hallmark of Alzheimer’s disease.We previously showed that neural stem cell-derived extracellular vesicles improved mitochondrial function in the cortex of AP P/PS1 mice.Because Alzheimer’s disease affects the entire brain,further research is needed to elucidate alterations in mitochondrial metabolism in the brain as a whole.Here,we investigated the expression of several important mitochondrial biogenesis-related cytokines in multiple brain regions after treatment with neural stem cell-derived exosomes and used a combination of whole brain clearing,immunostaining,and lightsheet imaging to clarify their spatial distribution.Additionally,to clarify whether the sirtuin 1(SIRT1)-related pathway plays a regulatory role in neural stem cell-de rived exosomes interfering with mitochondrial functional changes,we generated a novel nervous system-SIRT1 conditional knoc kout AP P/PS1mouse model.Our findings demonstrate that neural stem cell-de rived exosomes significantly increase SIRT1 levels,enhance the production of mitochondrial biogenesis-related fa ctors,and inhibit astrocyte activation,but do not suppress amyloid-βproduction.Thus,neural stem cell-derived exosomes may be a useful therapeutic strategy for Alzheimer’s disease that activates the SIRT1-PGC1αsignaling pathway and increases NRF1 and COXIV synthesis to improve mitochondrial biogenesis.In addition,we showed that the spatial distribution of mitochondrial biogenesis-related factors is disrupted in Alzheimer’s disease,and that neural stem cell-derived exosome treatment can reverse this effect,indicating that neural stem cell-derived exosomes promote mitochondrial biogenesis.

Influence of Topography on the Distribution and Structure of Woody Plants in the Senegalese Sahel (Sandy Ferlo)

This study describes the floristic composition and structure of a woody stand in the Senegalese Sahel, paying particular attention to the edaphic factors of its floristic composition. A stratified inventory considering the different relief units was adopted. Woody vegetation was surveyed using a dendrometric approach. The results obtained show that the flora is dominated by a few species adapted to drought, such as Balanites aegyptiaca (L.) Del., Calotropis procera Ait. and Boscia senegalensis (Pers.). The distribution of this flora and the structure of the ligneous plants are linked to the topography. In the lowlands, the flora is more diversified and the ligneous plants reach their optimum level of development compared with the higher relief areas. In the lowlands, there are a few woody species which, in the past, were indicative of better climatic conditions. These are Anogeissus leiocarpus (DC.), Commiphora africana (A. Rich.), Feretia apodanthera Del., Loeseneriella africana (A. Smith), Mitragyna inermis (Willd.) and Sclerocarya birrea (A. Rich). It is important that their reintroduction into reforestation projects takes account of their edaphic preference.

Boosting Adversarial Training with Learnable Distribution

In recent years,various adversarial defense methods have been proposed to improve the robustness of deep neural networks.Adversarial training is one of the most potent methods to defend against adversarial attacks.However,the difference in the feature space between natural and adversarial examples hinders the accuracy and robustness of the model in adversarial training.This paper proposes a learnable distribution adversarial training method,aiming to construct the same distribution for training data utilizing the Gaussian mixture model.The distribution centroid is built to classify samples and constrain the distribution of the sample features.The natural and adversarial examples are pushed to the same distribution centroid to improve the accuracy and robustness of the model.The proposed method generates adversarial examples to close the distribution gap between the natural and adversarial examples through an attack algorithm explicitly designed for adversarial training.This algorithm gradually increases the accuracy and robustness of the model by scaling perturbation.Finally,the proposed method outputs the predicted labels and the distance between the sample and the distribution centroid.The distribution characteristics of the samples can be utilized to detect adversarial cases that can potentially evade the model defense.The effectiveness of the proposed method is demonstrated through comprehensive experiments.

Diversity of Orchids in Terms of Their Distribution, Uses and Conservation in Annapurna Conservation Area of Nepal

The Annapurna Conservation Area (ACA), the first conservation area and the largest protected area (PA) in Nepal, is incredibly rich in biodiversity. Notwithstanding this, orchids in the ACA have not been explored enough yet thus making the need for ambitious research to be carried out. Previous study only included 81 species of orchids within ACA. This study aims to update the record of species and genera richness in the ACA. In total 198 species of orchids, belonging to 67 genera (40% and 62% of the total recorded orchid species and genera in Nepal) has been recorded in ACA. This represents an increase of 144% in species and 56% in genera over the previous data. Out of the 198 species, 99 were epiphytes, 6 were holomycotrophic and 93 were terrestrial. Among the 67 genera, Bulbophyllum (17) species were dominant, followed by Dendrobium (16), Herminium (10), Coelogyne, Plantanthera (9 each), Eria, Habenaria, Oberonia (8 each), Calanthe (7), and Liparis (6). Fifty-six species were found to be ornamentally significant and 85 species medicinally significant.

On-Chip Micro Temperature Controllers Based on Freestanding Thermoelectric Nano Films for Low-Power Electronics

Multidimensional integration and multifunctional com-ponent assembly have been greatly explored in recent years to extend Moore’s Law of modern microelectronics.However,this inevitably exac-erbates the inhomogeneity of temperature distribution in microsystems,making precise temperature control for electronic components extremely challenging.Herein,we report an on-chip micro temperature controller including a pair of thermoelectric legs with a total area of 50×50μm^(2),which are fabricated from dense and flat freestanding Bi2Te3-based ther-moelectric nano films deposited on a newly developed nano graphene oxide membrane substrate.Its tunable equivalent thermal resistance is controlled by electrical currents to achieve energy-efficient temperature control for low-power electronics.A large cooling temperature difference of 44.5 K at 380 K is achieved with a power consumption of only 445μW,resulting in an ultrahigh temperature control capability over 100 K mW^(-1).Moreover,an ultra-fast cooling rate exceeding 2000 K s^(-1) and excellent reliability of up to 1 million cycles are observed.Our proposed on-chip temperature controller is expected to enable further miniaturization and multifunctional integration on a single chip for microelectronics.